{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<tensorflow.python.client.session.Session at 0x15aee063fd0>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "from keras.applications.vgg16 import VGG16\n",
    "from keras.models import Model,Sequential\n",
    "from keras.layers.convolutional import Conv2D\n",
    "from keras.layers.recurrent import GRU\n",
    "from keras.layers.core import Reshape,Dense,Flatten,Permute,Lambda,Activation\n",
    "from keras.layers.wrappers import Bidirectional,TimeDistributed\n",
    "from keras.layers import Input\n",
    "from keras.optimizers import Adam,SGD\n",
    "from keras import backend as K\n",
    "from keras import regularizers \n",
    "import tensorflow as tf \n",
    "from keras.callbacks import EarlyStopping,ModelCheckpoint,Callback\n",
    "\n",
    "def rpn_loss_regr(y_true,y_pred):\n",
    "    \"\"\"\n",
    "    smooth L1 loss\n",
    "  \n",
    "    y_ture [1][HXWX9][3] (class,regr)\n",
    "    y_pred [1][HXWX9][2] (reger)\n",
    "    \"\"\"   \n",
    "    \n",
    "    sigma=9.0\n",
    "    \n",
    "    cls = y_true[0,:,0]\n",
    "    regr = y_true[0,:,1:3]\n",
    "    regr_keep = tf.where(K.equal(cls,1))[:,0]\n",
    "    regr_true = tf.gather(regr,regr_keep)\n",
    "    regr_pred = tf.gather(y_pred[0],regr_keep)\n",
    "    diff = tf.abs(regr_true-regr_pred)\n",
    "    less_one = tf.cast(tf.less(diff,1.0/sigma),'float32')\n",
    "    loss = less_one * 0.5 * diff**2 * sigma   + tf.abs(1-less_one) * (diff -0.5/sigma)\n",
    "    loss = K.sum(loss,axis=1)\n",
    "\n",
    "    return K.switch(tf.size(loss)>0,K.mean(loss),K.constant(0.0))\n",
    "\n",
    "def rpn_loss_cls(y_true,y_pred):\n",
    "    \"\"\"\n",
    "    softmax loss\n",
    "    \n",
    "    y_true [1][1][HXWX9] class\n",
    "    y_pred [1][HXWX9][2] class \n",
    "    \"\"\" \n",
    "    y_true = y_true[0][0]\n",
    "    cls_keep = tf.where(tf.not_equal(y_true,-1))[:,0]\n",
    "    cls_true = tf.gather(y_true,cls_keep)\n",
    "    cls_pred = tf.gather(y_pred[0],cls_keep)\n",
    "    cls_true = tf.cast(cls_true,'int64')\n",
    "    #loss = K.sparse_categorical_crossentropy(cls_true,cls_pred,from_logits=True)\n",
    "    loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels = cls_true,logits=cls_pred)\n",
    "    return K.switch(tf.size(loss)>0,K.clip(K.mean(loss),0,10),K.constant(0.0))\n",
    "\n",
    "\n",
    "def nn_base(input,trainable):\n",
    "    base_model = VGG16(weights=None,include_top=False,input_shape = input)\n",
    "    return base_model.input,base_model.get_layer('block5_conv3').output\n",
    "\n",
    "\n",
    "def reshape(x):\n",
    "    b = tf.shape(x)\n",
    "    x = tf.reshape(x,[b[0]*b[1],b[2],b[3]])\n",
    "    return x\n",
    "\n",
    "def reshape2(x):\n",
    "    x1,x2 = x\n",
    "    b = tf.shape(x2)\n",
    "    x = tf.reshape(x1,[b[0],b[1],b[2],256])\n",
    "    return x \n",
    "\n",
    "def reshape3(x):\n",
    "    b = tf.shape(x)\n",
    "    x = tf.reshape(x,[b[0],b[1]*b[2]*10,2])\n",
    "    return x \n",
    "\n",
    "def rpn(base_layers):\n",
    "    \n",
    "    x = Conv2D(512,(3,3),strides=(1,1),padding='same',activation='relu',\n",
    "               name='rpn_conv1')(base_layers)\n",
    "    \n",
    "#     x1 = Lambda(reshape,output_shape=(None,512))(x) \n",
    "    \n",
    "#     x2 = Bidirectional(GRU(128,return_sequences=True),name='blstm')(x1)\n",
    "\n",
    "#     x3 = Lambda(reshape2,output_shape=(None,None,256))([x2,x])\n",
    "#     x3 = Conv2D(512,(1,1),padding='same',activation='relu',name='lstm_fc')(x3)\n",
    "\n",
    "    cls = Conv2D(10*2,(1,1),padding='same',activation='linear',name='rpn_class')(x)\n",
    "    regr = Conv2D(10*2,(1,1),padding='same',activation='linear',name='rpn_regress')(x)\n",
    "    \n",
    "\n",
    "    cls = Lambda(reshape3,output_shape=(None,2),name='rpn_class_reshape')(cls)\n",
    "    cls_prod = Activation('softmax',name='rpn_cls_softmax')(cls)\n",
    "\n",
    "    regr = Lambda(reshape3,output_shape=(None,2),name='rpn_regress_reshape')(regr)\n",
    "    \n",
    "    return cls,regr,cls_prod\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "import utils\n",
    "\n",
    "utils.get_session(gpu_fraction=0.3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import utils\n",
    "import numpy as np \n",
    "\n",
    "\n",
    "\n",
    "inp,nn = nn_base((None,None,3),trainable=False)\n",
    "cls,regr,cls_prod = rpn(nn)\n",
    "basemodel =  Model(inp,[cls,regr,cls_prod])\n",
    "\n",
    "\n",
    "basemodel.load_weights(r'E:\\deeplearn\\ctpn2018\\model\\weights-densent-09.hdf5')\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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VVdVxtRB9ZTReiY3sj9AfeSsa2ALcAdSBSU3THgHuAm4FLgRqgKWaptmUx/4X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\n+eUEAgH27NlD69atufXjj/H178+mK65g9erVWJZFbW0tz7/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Xa5cGcAjSzJkzaWxspKys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4RJUE1iLJ8zx2Ry4iZH/e/CCRMqy7L6ASuBRJwqP5NcYjMCsHE4KAklOAQMoA0Qsm276hue+d6h\nuRNRWsKefOIJ/X9CQgL93nyT9jt28LZbnUVt5Ktnz2b59OlsHzgQy7J0yfXf33GHzlPe2NhIQUEB\n/fr14xc338ys666jT58+bN26lT59+pCUlMTPrrtOuzNEo1E2bNhAr169uPWXv6S4d+8YD2+vkV1B\nKkgVskkxSop+SqST6YfVHMgNrpBU+hZJBajU1UinQXktHouvEFu6Uqh1UGNo7tSXRMG8bxIxqU9S\nY5GE2+QUZb8ArSuSHI5JIMy4R3O8krhIZb7JxcTTn6n5UXOt2pIcqlSSy/eUQl2OVRKUeByN+j+e\neiAe5yrHZEoe5prJdTXX4tssic3ByXBU24ABQDowBfgfy7LGnNTX/5dALop53RaL/sQTT1BaWorP\n5+PGI0cY5/Fw1113kZaWxq233uqIZ8CRI0eAJvPtq6++yu9Fu5Zl8dZbbzFs2DAA5s+fz3nnnceS\nJUvYv38/559/PoAWmzweD9u3byczMxOAkpISsrOzY1h41a76LcVMqUyPRmOLNSjEUtY6dXJDky5L\nuic0NjYSCAQIBoPNulHEA8mNSeSVnJu5URRI5DW5OtlPk+uTHJ8URdX4JRcluT5o8juL50Kg/v6m\nlLvxcCoe8VVjkqJZvLbUuqn00eq7kgjJDBtS7ynnWH7PJOjqXryDWzpymgRKgZovKWabnKmpjog3\ndycDJ0yobNtuBHa7/663LGsYjm7qQcDC4ZokV9UGWO/+fRjwW5bVwuCq2rj3vhFuvfVW0tPTY65N\nmzaNadOmfWu/5UklxqInbtu2bfh8Pl3+2y4txettCuYtKChg0KBBgFN4ssy2mT17Ng8++KDeGMXF\nxbRs2ZJ1bqrilStXMhNnU/Ts2ZMvv/ySc889Vy/uu+++i8/nIxgMUlhYyKFDh3gAh7BdcsklOvj5\n25ZWErJv0vHI8uPx9B0KCVXoTTxxozmDgyQgkqhJvYa5HpLYNDcm1bZJAOJ57EtuwlR2q02mQBFk\nSejkt+XmlYeA7JNJuNV4Taur7Ie5ueW9YDCoc2ZJ4qy+o7g+qTOV/TUJkpwTk3CZovC3iWfqvowp\nlXgldX/m+Gzb5ssvv2TlypVYlsUrr7wCoEvYfRf4PvyoPEDAtu0iy7IOA+cAG93BtQB+ADzpPvsV\n0Og+s8B9phfQEUec/EZ45JFHTqqun1oMU4krJ7umpoZevXpRWlpKhw4dSCkqIsGyaNeuHbm5uYRC\nIdauXcu0YJClS5ey/dgxfD4f+fn5bNq0CYA9e/bQunVrXbm3i1v1tl+/fuTn5zNgwAAef/xxbnOL\nXY4dO1Yjb1ZWFpWVlbB9O1deeSUpKSlNiC2QLx5rbXrOm8gp/4/H3ag5iqe3keKV+qacQ5O1N10L\nFCcnvytFKrnZpPgm9UpSryitaQpMHyfFDap2TVDERFrUZF/kPCoxWM6PyWUqb3rZN3VoSKKt5sDM\nPSY5GOnZLp05FZclRUspgkoiKhX1Uv+o+qTuSRxR7SjibFpMTdHeFGHlusdb25EjRzJy5Ei8Xi8/\n+clPgJi6ft8KJ0SoLMu6H/gA2AekAT8FzgTGu4/8HccSWAjsAe4BDgAL3Q5XWZb1IvCwZVkVODqu\nx4AV9n/I4uf2+7iJN0/oAQMGUFFRQVlZGaWlpTRGIkTdic7Ly9OLFAgE6D9gAK9v2EBNTY0ugU5B\ngUaq6upq6urqWLJkCXcAO3fuxOv1kpiYSHJyskbM1157TYtlY8eO5euvvwacbKNqc5jjMBFLnooK\npGgn9UPqPbO+m+QOzNPVRDpTn2Fek/+r903RTs27GTak7pvigymOyHck0VMEw9TlKGKh1lwSQpMr\nMUFudHPjKkImayTKrKIyFEnOYTw9kPlNqe8yuTK5tnJeJIcniW887k+uhXxOPmPiR3Ocl1IZSI5N\nQnNi4InAifpRtQbm4OipPsHxpRpv2/YSANu2HwQeB54FVgNJwPm2bYdEG7cC7wFvAp8DxTg+Vf9R\nMDezRkx3UgOBAD6fj9GjRzNo0CDOGDyYzIwMzj33XKqrqwkEAprIpCQnM3v2bBISEhg9ejTl5eUA\ntGjRAtu2WbJkCS1atKC4uBhoWkiz6MM111zDkSNHuOmmmxg6dCiHDh0CYvM6uX8cNxapm2hufJIz\nkJZP+Y656aWYZIo6JnEyEVBuPvWsqS9SG0YSy3iin9knyT2q9qQ/lqnbkgRSKpNlnyVHIEtMqfdN\noqa+q35LLseME1R9iScGqfWTnKC5DsrfSbYl19m2bV2BxyQgktOVYqLZFyllmCKsFJUlkZLcmMnh\nS9VDvHmQhPVE4YQIlW3bM23b7mrbdpJt2zm2bWsiJZ65y7btXNu2k23b/qFt24XG/aBt2z+3bbuV\nbdtptm1fatt26Un1/juCrHVngpq2aDRKSUkJR48epbq6WrPnR44cYe7cuVp3A44SvLCwEL/fT2pq\nKsnJyYCTSK+mpobzzz8f27aZNWsWAGeccQbl5eUMHDiQ3NxcGtxSXIrwpaam4vV6adWqFUBT6XRl\n7TNOU2WZNBFFIZ8ZEgRN4tA3cRBmql6JVOrEbK4On6kbkv1RfTI3k+qn6aAq10o9Y9s2wWAw5tty\nrJL4yrakNc3kQCSnJXVCso/qmumXJvspiZpMoRyPw1HvqcPLBKlbklVu1Luy/yaRl172sp+KoMn3\nzLbkGkrCbhoazH6rNZBcu4lX8YjxicIpkeFTyvLNQTQaZe/evXz44Yd8+OGHbNu2jSNHj/LZZ5/p\nRVi3bh319fWszs+nsrKSaNQJgRg1ahQAf/3rX0lPT2fo0KFaTASnFFePHj3YtGkT5513nvZF+vLL\n/4+9946vqsr+/t/ntnQSQiCFkISEEqQjRZp0sNCUIiC9iYoKKopiGXBGkRGxoyICIo6DgIhYKCpF\nBaRILwFCQhICJCE99+bm3nueP87dO/te4szozPd5vr8fs14vXiQnp+699tqrfNZaP1NSUsLcuXNZ\ntmwZj3qhEOfPn+eFF174zXcWTFyTyaWaACJipPo8fmtHU6EG/kJONR+Fk11dJCqjq2ZLTQurpndV\n50csNrVJgvhm/x57QtAI7UPVQNT7+vukajLBxHuJsVUXlxhDVVtThYL/d6lak3qtEBwq9MP/e0Tk\nEqojk/5j5S881G9Wha94H/UZ/uaravILwatu7OpGIeZEFcjiWUJ4qTAPQf6C8Y/QDZOUrDqUxTH/\nneLatWuSOaw2Gyalq4jH4yE5ORmbzcYdd9zBuXbtOHbsGC+++KK8Z0JCAmazWe78WVlZAERERDBx\n4kR++uknFi1axP333w8YAmnOnDk0aNDAZyGsWrWKyZMny+ib+h01oa7BNzHWP7dKCBhB6m6sLjJ1\n4fozuNAc1E4wqrD6LeiCKgDU54jrVMEkvtd/JxdCSiwI1bxQNaKasFz+DnCTySSR5+qYie8VieL+\n/KLyiXie6kBWz1MFtiqg1Xfzx1j5m4TqXPkLPvX+6reJc2oC5YqxU//mn0KkjpG4TvXtCiHpP/+q\nL1Q1Rf3H5B+Z+P+MbghB5a/210RVVVVMmDBBTk7rDRuIO32aBx98kIKCAjRNIyIiwmdHe+CBB+QE\nMWUKw4cPl4z+xBNPEB0dDcCAAQOorKykdevWtG/fXk7YhAkT5AJWGXTRokWUl5cTGBh4ne9AMI4/\n8E68hz9zqYvcX5AIRldrtauCpSbzQPV/1ET+vgzx3jWNvf9xFUgqFoS/L04sOHXHVnMu/d9V/WYB\njlRNNxUXJAR6TcBUcV9V4KpCS13s/hqPmrOnClqVatI4VMFRkyPbX5j7By7858Uf+OmfS+gvOP3f\nz388xM9CsIu58id1Hv8o3RCCSlBNgy3okVmzrjv/UkoKFouFmJiYag0GJFzA7XbjcDiuA1jquk54\neDjl5eVA9QK0Wq0+2tCIJ5+8zmQAmOjtaqOSS4mQ+YeF1SiXWCxCqAkmVxndXxtT/RfifFU7Ec+p\naQz9TTr1/uJnf6Ej7qPeSzUvhfmjak7qPf2FqJpD6a8pi3FQx0TVdMRiVcdVNWf8N7iaFrX/mKpa\nm67rPlUQ1PmpyTxSxxZ8C+L5j7tq2gpttCb/kKol+28g6uanPl8d85qEU02amKo1+Qt38R1/FJmu\n1aSu/28jTdPaAQcPHjz4h3BUq1evpqioyGcHVAfMX0U3mUzUycxk5Msv/we/wpfKatfmwMCB0pkv\nZuFq48aUxMZeJ0xU08ZflVZ/VxelYEhxnroQVcZUGVn4KNTdVhV4wnwQxwWpC1hV/VXflyrY1GPi\netUhq75vTaSaIUJTUhOfAZ+KpOq3q7Wh1I1D/QbVpPTXBMQxlW9qErz+gt7j8VwHOxFCJiAgwEeb\n9X9PITTFt6p+PRVzpfJHTdqRGCNBYnw7L1/uwzc+m7mfjLBWVpKwd2+N87Lm44+v28RUPjWZTIwa\nNQrwwVHdrOv6oRpv6KUbQqMSA66qxuqOUZNZUpCYyNJ33vHZbf0Xv2oGqYtZMKZYCOJ8deJq8mto\nmkbKvn1EZWZe9/7nOnb02Q3Fz8n79hmMpGk+DHXOW9NdFUa/5UfyJ3/NQo2a1ZRSIsazph35nwkb\ndTH7R6b8BYL4mxhrcVw4cAWqW4yP+F01l9VNSjzb4nDQ4Ndf8ehGSpVmMqEBDX/+mQZeMO//30nX\nNDJuuQWPAjKNPXMGZ3AwhUlJ1ed5PCTs3cum116j1BulFjw9dty467Tsf8cvpdINI6jUgVMXn8fj\nIcxup9LhIDg4WO7CFRUVBAQEGNqF1SpzAsUkgi96O+X4cXp88sl/5H0rwsLQqNayzC4XvT74oMZz\nXTYbVYGBPseCSkp+8/z/Us3kCA1F99OcgkpKWPb++wR6x1doe5MmT2blihU+Wp2u64yfMIE1H38s\nNVK32421qIjRjzzCG6+/TnBwsNSKWn/+OTEnT/LB+PFER0ejaRo2m42RDzzAj6NHc7FzZ6kdinv3\n7tWLMWPG+JijkyZPZtXKlXz44YeMHTuW7OxsmjRpwr1jx7L6o498oqVut5vxEybw10WLiI6OljCY\nBkeP0uPNN/nLTTcRFxdHcnIyS5cuZV18PCXx8RwdPx673U5YWBg5OTnM2ruXjIwMAgIDycnJoVmz\nZnLM/LU3tXy1mmHwe+mGEFT+drMgTdMIKi9n0tNP/0ee8+mzz5KXl0fdqCh0ICcnh8dXrOCdt9+W\n/pDS0lLS09N56+23mTJ5Mq1bt2bPnj306dMHj8fD9PvuY83ixWiakX6yfft2RoaEMPzTT/nQ29ar\nsrKS3bt38+qpU+RGRrKkfn169+4t32PqtGlsfewxztnt5OXl0bp1awCGPvMM49q25a677vJxKA99\n5hm+fOklNE3jwoULJCQkoGkag59+mnlDhpCamkpISAhfffUV/Tt04J633mLjn/9slGH2Lpqm27cT\nlZ7Oj9OmyfdwuVwMevllTg0bRnqTJmRmZvLFF1/w4IMPMmL+fD5/4QXASF/aunUrDRs2ZMGGDTzU\nqxf5+fl07dpVLqgxL77I3XfdxZUrV6hfv75k/L+vXcuqlSspKCjg/PnzdOzYkYRjx+jy6qusevdd\nudnouk7/116jLCGBzzp14pVXXmHKlClkZmby+caNbH/xRfJCQyWPBAcHM/Keezh16hROp5N27dr5\nmID+YE3BY6dPnyYlJUVGft1ezJzD4ZBwlbS0NNp5tbq///3vPPbYYxw9epSrV69yt8vFpk2b6NSz\np3G9ogEGBQVx4sQJ2ngrd6hYM7vdjq7rREVFsWrVKu4FCgsLiYiIIDs7m4yMDFwuF+OBw4cPExMT\nQ25uLh06dKC+V7js2bOHTp06kZWVRUxMDHn79pHtcLBjxw66du2Kw+Hgww8/ZBYQGhqKbrEYCfnz\n5smAzG/57kRE0D8i+a/SDSOoVKcqKGhZL2O++cYbHD58mKKiIq5evcq4c+foWFbGYx07MnjwYMmY\nk+fM4c1mzfilYUOcTicBAQFcunSJn/fs4WpUFB9s3Mj48eMxm83UbdQIVqzAZpRhAJEAACAASURB\nVLNht9vl4hKI9d27d3Pp0iUOHz7MsWPHZA6U0PaCg4M5cuQIj48a5eO/CAkJISsrC81kdIa5dOkS\naWlplJaWkpKSAsDzH3/MwIce4prFwq6CAurVM6o9H3Q46B0fT3p6OqWlpXz66acMBdafPk1GRgbt\n27fHHBEhQazNR47kySefZOHChVwIDkZLTQWgMC7Ox59jDwvDHRBAUf36voNvNrP9zBkKExLYe+EC\nZ202tl26xAigNCEBu91OeXAw+dHRWL0J581HjmTRokX069CBIrebffv2MQYIDAwkNzeXxMREXC4X\nV64Yue8mk4nw8HAiIyPJy8vj2Ndf09U7fhkZGdSvX58jR45wS0kJx48cobxFC2JiYkhKSpIBD7vD\nwS4vTk74g0YCFy5c4MKFC0RERNCoUXVVbXGO8OUVFBQA0KhRI0wmE5cvX8Zut1Pba85mZWXJpPXI\nyEgqHQ6Ki4oYPWsW69ato1atWvTr1w/rF18QGhoq7+90OiktLQVg1KhR7Nmzh23btnHnnXdit9sB\nOHLkCAMGDOD06dO0bNmSfv36wbZthIeHo+s6CQkJMh8VoKKigoKCApxOJ/Xq1cOUnY3L5SIqKoqb\nbrqJo0ePEhUVhcW7Xrp164bb7SYgIEBivBwOB6X5+ddlUQiBpLoaVP/pH6UbBvApdj3VYeiPxM7O\nzqZ///5MmjSJm2++mejoaIYOHYrJZCDBDx48SKXTidliISAggMjISE6ePMn48eMB2L9/P1VVVaxf\nv5733nuPjRs3ArBixQq++OILcnJy2Lx5MwcOHAAgNjaWfv36kZqaysSJE6lbty5gVE9Yv349H330\nERUVFXz77bd4PB62bdvGtWvX+OSTTzhz5gzZ2dlYrVaGDh1KfHw8Bw8elAzTrl07MjIyyM3NJTAw\nkKCgIMAQdA6Hg5SUFFq2bCkZrUWLFsTFxdGoUSNZ5kW8S2pqKs8++yy1a9fmm2++AXwbYqh4LPG/\niPJ5PB7atW3L4cOHmTZtGmFhYfT0agtgIP8dDgcOh4PGjRsD8MQTTzBu3Dg5XwcPHgSMBZaSkkKT\nJk3QtOqu1Pn5+aSlpXHkyBEuXboko5xfffUVmzdvxu1206pVK2w2G+07dMDpdNK9e3cuXrzIqVOn\nALBZrfTu3Zs777yTu+66i0GDBgFGdY7HHnuMJk2aXOfz83g8lJWVYTab+cRr9rvdbpxOJzExMSQm\nJrLH63SOjIzEYrEQHR1NTEwMZouFa4WF7Nq1C4vFQtOmTfnyyy9xOp3y/Z1OJ4cOHeKjjz4C4MCB\nA5jNZo4fP86TTz4p333btm24XC66du3Kvn37ZLkgwft79uwhLCxMHg8NDZWZD2vWrJE8EB4eTkhI\nCD169KB9+/bUCg+nbr166LougwBCUJ09e5aTJ0/Kig9iIxUCVvgXVT/svxO4uyE0qppI4FkE44nw\n7rp16wgKCiIwLQ3TlSssX76cCRMmUFhYSGhoKEFBQegeD5cvX8ZsNlNYWCgno3v37pw6dYqRI0di\nsVhYunQpYOyEIqqTl5dn7L5ZWZSWlpKXl0fTpk05dOgQt95qlPUaO3YsJpOJ7Oxs3G437VNTMR89\nauyUwN13383Vq1ep43Cw49gx7HfcQVZWFkFBQYSFhQGG4D1x4gRut5v09HQpHCwWCxaLhStXrkjh\nBYaZUF5ezvHjxwkKCpLaw6BBg7BYLCxbtowhQ4ZgKSyEr76Syb8i9K7rOv7eh/LyclwuFz/9/DNV\nsbG8/fbbVFVV8cYbbzAGo8xH/fr1qays5MiRI6SlpfEU0LBhQzIzM/nmm2+YOHEis2bNgokTCQoK\noqysDJfLRVhYGPW92ltISAjJycnk5+ezd+9eOnkFSp8+fVjp7WgdFhbGpUuXOJefT+GQIYSGhhIR\nEUFERITBD24327dvp7S0lKysLCIiIhiHoTkI7BVcn5Qtvl3kewoclsvlYteuXcTFxgKGuSdM0MuX\nL9MKQ/sqKirikUce4fjx4/Tp0wfr1q2AkXt67do1mjVrZkTGpk2jffv2mEwmmjRpQmhoqIzeTZky\nhezsbOx2OxkZGdKnJgRDp06dMJlMnDx5Us5NgwYNOHjwILNnz6Zs3z4JVLZarRJyYzabCfFq1sLX\npeLzRBTYH+Pln7ngD7r9I3RDaFSC1NC8qmVBNYONHj0ak8lESnIyDrudsWPHYrVaiYiIoGnTpui6\nkZoSFBQk/R/CfNA0DYfDwYEDB/joo48kMv2vf/0r33zzDRaLhV27dsmaWk6nk/DwcDRN81Grjx49\nyhNPPEFeXh4xMTHk5+cDyGetWbOGvLw8ysvK6NChA9HR0bRo0YKoqCifiFazZs0IDQ0lOTmZxMRE\nwGAawYSBgYFUVFQAUKdOHXRdp0WLFqSmppKRkQHA9u3bWb9+PadOnWLTpk388MMPABQVFWG326uj\nb1xfNys0NBSr1UpcbCyjR49G0zTuv/9++vc3im0EBATw+uuvs2bNGlq1akWXLl0Ao3BgcXExrVq1\nIiQkRN6voKAAs9nMsWPHuHDhAlu9i1rMYWBgIBMmTJDjeOnSJenr27JlCxHh4XTp3Jm4uDiSkpLY\nsmULycnJcmx79OhB//79iYqKYsSIEYBRuketCe+PqRJO81q1agFImMQvv/xCVVWVnOuWLVsSGxtL\nu3bt6NevH26Ph3PnzlFYWMiPP/4IGNqr0+mUWllERAQ2m40VK1YAcO7cOZlepQZ1TCYTDocDt9vN\niBEjWL9+vRwXh8OB2Wxm48aNLFmyBDAE++XLl5k9eza6rhuCTTfAqIGBgbz11lsUFhYa5vXVq1Lo\nFBcXM2yYUT9gx44d9O7dm1mzZrFhwwY5BzXhr8T1/ik8v4duCEHln+bhj0cCQ8iUlJRgt9upqqqi\ntLSU2qKInrJ7aprGuXPn0DSN4uJiAgICpJN06dKlBAQE0K5dOxITE3nxxRcBuPXWW+nduzcFBQXc\nfPPN8vzevXvz1ltv0bBhQ5/Qf/PmzbFardx0003ceuut/PTTT0A1grxr166Eh4dTp04digoLeeON\nN8jKyqJZs2aSSS5cuECLFi2Ij4+noqJCXltVVUVVVZU0RUJDQwFkDS0wGEyYYX379sVkMhk7b1kZ\n3bp1A4xKEU6nk3nz5hlVIbwalbrjiuRYj8dDaWkpLpeLyspKysrK5DMffPBBJk6cSGVlJUneMHhQ\nUBDJyclke30n4p6pqak0b96c+Ph4UlJSfISvxWIhMzOT3bt34/aa9A6Hg5tvvhlN0wgLCyMmNpaS\nkhIuXrzIli1byMvLk8XbLF4BHxwcTHl5uTTP165di8lk4vjx4z4bm4prczqdTJw40biPNwugXbt2\ntG3bVp4vEsJFQrqmaSQkJHDPPfdw5coVysrKuPvuu32ap4pqn2KOEhMTadiwIVFRUTUmkNtsNtas\nWSNxSgIM/NVXX9G1a1fppwwODub06dNs2rSJrKwsI5pJNQTH4XBQWFhIZWWlrDpqs9l48803iYkx\nKoY/9dRTuFwujh07RklJidysa4L91ISq/710QwgqNYtcHUiVNE0jPz8fXdcZOHAgBw8eJDw8XJo2\nFouF4uJiKisr6dChA5qmcfnyZZ544gl5j+nTpxMREYHH46FJkyZyZxNRGjCK5YlJBUOT+/HHH4mM\njJQLuLy8nLKyMjZs2MD+/fslg23atImQkBCaNm0qJz+idm3q1atH06ZNSUpKus4nYPdG/oSJoyai\n/vLLL9x5552AsZAcDoePKQwGKA+gfv36NGvWTPqoPB4PAQEBhIeHY7PZMGkaOtUod7nYKiu5fPky\nmzZtYtKkSURHR5OebhSILS4uRtM0SktLsVqt0pSrVasWrVu3ZuTIkeh6dcWGhIQE4uPjSUpKIjk5\nWY7XxYsXeeedd+jSpQu33norlZWVmM1mbDYbFRUVnDx5ksaNG+NyuYiIiKB79+7k5OQwb948Tp8+\nDRiLeunSpbz//vt069ZNVnMdPnw4r7zyChkZGT5+FvGzxWIhODiYOnXqALBv3z7pm3G5XPJbDx8+\nzIkTJ9izZ480ga9duybn88qVK+zfvx+3y0Wl08n69euv0+B+/fVX4xyvJqWm+qSnp/Pxxx8zduxY\nWrRoAcCCBQu4fPkyffv2pVatWlLbvvnmm5kxYwYtWrQgPz9fVn0NCgrC7XbTqFEjmjZtSmhoqNTA\ni4uLGTx4sNQQ169fz/Lly/F4PIwZM0a6HATVZLWo5uDvpRvKR6VWS1SdvgCZmZnceeednDhxgg0b\nNvBlr15kbN/O+++/z6BBg0hJScFkMhEYGMip06fJionBbrezf/9+WaXwwoUL5OXlERQUhM1mk07g\nv//97zRq1IguXbrgcDikdrNq1Speeuklvv76a3bu3Enfvn3l+QsWLCAoKAiXy0Wj8HBcx46xc+dO\nevXqxVtvvUVERATF165x9MoVjplMvPHGG5SWltKyZUsmA529ZlRAQAAtW7aUzvFr165htVr59ttv\n0TTNeOa771JeXk5RUZFcHCKKZbPZuOuuu7Db7bRo0YKkkBD4/nsyMjKIiYnhnnvuMVR6XZeAU5HI\nbTabsVit9OrVC0etWixbtoyMjAzJrAUFBURERLBhwwbatWsnI41C+1BzF6HalNR1neLiYukcjo+P\nZ+bMmVRVVREcHMyAAQPg008JCgqicePGREVFScGbkZnJoUOHmDVrFi6Xi5kzZ8L48dhsNqZOnYrV\napVYOjB8OY899hhHjhzxAdyqzTdU7aZt27ZUVFQQFBREnTp1uO2222DrVgYMGCAjXz179iRg3Trq\n1q1LTEwMUVFRNG3aFADzxo2MHDGC9A4dpGN62LBhsHUrbdu2ldqaCpCNiopi7NixPvW5AF5++WWZ\nfmM2m3n++edh3Dg5P4mJiSQnJ+M+fBhN0xg2bBi6rjNhwgQZeY6KiuKiphESEsJNN90kv3PChAmU\n1KnjU9YGfLMJaoIF/dF8vxtCUP2WY08dwMLCQjRNIzk5maeeegpt61aSkpIYOXIkwcHB5Ofn8913\n3zGzqoo7br+dpJYtCQoKIjc3VwqkhIQEOnbsyOnTpwkNDWXRokXwwANMnjyZ0tJS+R433XQT/PAD\nf/7znwG48847KS4uln6Oe++9V6ZW6LqOw1tL6pFHHsFqtfLkk0/idDoJefdd2jRpwrzBg32y2fn8\ncxomJVFss9GxY0esVqvUPp566ilKSkro1q0bmqZJH1VwcDDjxo2T/hHxLiomSGgkYGhYVquVevXq\nVY+jMp7ChDF5IRTJyclMmTJF/o3Jk0lKSsLtdjNu3DifwMYDDzwg00RUUjsih4WF0blzZ3j/fZ+K\nCxUVFSRFRgLGAhYL2uoF7TaIj6d9+/ayEqdY7E6nE3NYGLquX1dpwuPx0KhRI58F2e+ll2rktTte\neaW6xpmuo3nv33/hQuN+3r+F5OdTERl5XS0nMc7CgS9gAeJd1HPVcsuapsl5EscFTEBAa9RUKuEC\nEdebXC76v/QSKNHb2hcvEpGdTaTXX6kab51efx23F5BakyNdDTT4Z0f8Ebohcv1WrVpFUVGRjyNd\nDF5AaSnT/kOAz/9JclksfPTee5IZNU3j9jffJFGJ5PyX/kv/r+nj1auB66u9CjKZTIwZMwb4b67f\ndVRTiReRxGkPCeH1117z6XsHvrgP/yRLFcymAtpcLpc01/wz41V/gqZpxFy4gNlkkk5oQUP/+tca\nv8HicjHZq5GodK59e4736uXjO9HUZ3u/VeSvqd/j0XUD8Kpp6IpPQWUyNVKKpmHSqrP1xbPMZrPM\nEVPNQIlZM5ulD8vj8UggodtjNK4Q2oFqtqh5eWq+Hso3AJRGR1MRGuqD9TGZTNQ7V11YVsxp+7/9\njbrnz9c4vr9FV1JSrlt00efPcyU5WWqQ4v71zp3jqhfWIRHZHg9RFy7I+6AbeZkhBQVY7XYKFYCs\npmlEpafz/ZQpZHXuLMfZ7XZz34wZrPRG/8R4mUwm7h07lo9Xr5aJzXjHeOy4caxauVLyoYDfiOPi\nPiaTifgjR7j1jTf42NuNW8x531dfpaxBA/aNHCnPd7lcTJk6lWtJSVR551UzmUDXiTp7Vj7f373i\n72r5vXRDCCo1RFpToqRA04pFAdeX0xDHBKkAUqFCq9cLmvHgg2i/c3KWvfEG6NV5iYmnTtFn+XJW\nLVniA1gdsHQpjQ4coJE3QvVf+ud0fMAADowahc1mo6ysDE3TmDZ9OmsXLqQ0KkqObWZmJvMXLGDz\nU0/J6JuAo0ydNo0tzz8v02U0TePatWs8PmcOX86di9VqlT6x8Koqht9/P1/OnesDgGy9YQOxp0+z\nZd48zp8/T0REBE6nk0deeIEqbwCnqqqK7Oxs2Tbt0qVLhIWFSZyTcGAL35fgl127djGW68u1LF++\nXB5/9dVXmTNnjg+/bty4kSFDhqBpGnv27KFFbi4h8fGYTCZOnTpFWloaJpOJKcBDsbGU1a2Lrutc\nunSJwYMH89zzz9c45v8J0++GEFSiqYJgQjUMH1RWxrR58/7JHf49euvNN6UPxmQykZeXx7xnnuHd\npUuxWq0UFBQQEhKCyWTi/gcewGOzGUyN198gGiQEBsqIlm4y4dE0jvXrx14v5kdoiVOnTePjBQtw\nxMZKnE6vXr2YNXs2S995x6cevNPp5OVFi3j2mWcoLCwkMzOTwYMHAzBt+nQ+WLaMlStXMnHiRNav\nX8+9/fsz9tFH+WDZMhluX7lyJe/Uq0f0iRP0DwyUvrSqqiomPv44S1u25EsvuFQ0wPhi0ybe9cI5\nrly5wqFDh+jevTsPPfww7737LkuXLmXEiBESrT/9vvtYuWLFdZgc8Y5ibk0mE3GHD9PnnXf46L33\ngGrtuN+SJWiaJjWv8+fPc/XqVaYBAYGBFDidBAUF4fF4+PTTT5nvvXbTpk3cfPPNhIaGEusFcGqa\nxrp165g/fz65ubmsWbOGx6muH+VwONi5cye5R48yHLh69SpZWVmEh4eTmZlJG0XD37JlC6NHj5ZB\nlgBvwURd14mJieG9995jKvDxxx/TqVMnIiMjMZlMRvcjqvtDpqenM2XKFAm5EHNQUlJCWlqa4dPb\nsYP09HRat25NSUkJhYWFJHjfQ4BWX375ZUaOHInVZsNRWYnT6SQlJYWEhAQj4LF2LbfffjumlBTc\nbjfFxcU+/Tb9zT1VSfivoPoHpEYfxD9VJQWjpbsw37Zv3859ubm0Lylh3cMPy91K13WmPfUU3w8f\nzvMnTjB9+nTp8J750EO8/dZbUi1fsWIF48eP58GZM6tNJwyt64MPPmAeho1usVjYvn0706ZNk3iZ\nffv2UVRUJAF47XJz6eXxUFlZKRejBNhRrempyGHx3Vu3bpUAVXFMOF6rqqp8kOwRERFERkaSkZHh\n8y7p6els3bqV48eP84PVyliM3b1u3bqkpaXRvn17cn7+GVthIS3795e7bN26ddE0jbZt2vBDTg5l\nZWUUFxfL8HlQUJDUDqqqqmQH6sOHDxMfH8+5c+eIiYmRzL1p0yYGDRokTVQViiFIV6KPqukuNqis\nixdZuXIltWrVYteuXbLe/bZt28gymxk0aBDHjh2TvsArV65w5coVUlJS2Llzp1yQ3377LRaLhZ9+\n+omAgACjJyMGlq5fv340btyY22+/nVMhIXDmDGazmSNHjjBjxgy2bt2KxQs0FS4HtRmnmGO73c6Z\nM2eMhPMDB7BYLGRlZZGQkMCVK1ckJuvuu++WAYMtW7Zw5MgRAJ599lmefvppGSAR8I/vvvuOcd7o\n3969e+ncpAlgJLvn5+dTXl5OSUkJJSUlHN69m4iJE3G73fzlL39h6NChjMNIuH9/5UqGDx/O6tWr\neUkJLvgLKn8r44/QDYGjUv1Juh8TCyYvKCjgq6++YufOnWRkZHD1yhWKiopYtmwZ5eXlPsKuuLiY\ngQMHsnz5cimoxD1FDpXZbPZJURHhdjVak5WVxdmzZ3E4HNSuXVsuvA4dOtCvXz9uu+02evXqRctW\nraS/wr8ulu6prt4phCkYsISsrCysViuDBw/mlVdeAapBo1988QXFxcWc9/psKioquHz5MseOHTN8\nPF7sVvfu3YmKimLgwIE0bdpUtqOPj4/H4/Fw5MgRmjZtyslTp3C5XLRu3ZqcnBy2bNkiy5QUFRVR\nWVlJdHQ0ubm5pHoTmwFKSko4ePAghYWFUtPbu3cvvXv3pnHjxjJfEKB27drk5eVRWVl5XTTJZwPy\n3tvj8WtUoevUr1+fESNG0LZtW26//Xa6d+8OQJcuXRg4cCBg5EmKZ2ZmZjJx4kTsdjuHDh2S4xsd\nHU3Hjh0pLy/n3LlzclxiY2NJTEykrKyMn3/+mZ07dwJIIVxZWekT4auqqiLTC5m4cOGCRPlXVlYS\nFBQkc+oAevbsScuWLSkvLyc3N5fLl43m4l9//TWzZs1i//79JCQkyPSnqKgoyWvBwcGyy1G7du0I\nCAggNjZWQjwE0POnn36ioqJCRqHFuAofV5s2bQAoKi4mNDSU5s2bG5UU/NaVIF33rfX+R+mGEVSC\n/IWVx/uz1WolLCyMXr160axZM+rWrUvt2rVlATaRC6V7PORdvUpUVBS9e/eWDAi+JYItFguff/45\nAC+88IJkUBWLExkZSXx8vNSEhBD55JNP+PTTT1m/fj3Lli1jz549uN1uPv30U+x2OwUFBUaKQ1UV\nlU4nRUVFZGVlsW/fPpmoeuzYMbZu3cqwYcNYsmQJc+bMkfcuKSnhzjvvxGKxSNiC0GhatWpFYmKi\n3AW/+OIL7rjjDoqKiigoKJAZ+yoQVvhQQkNDiY6OJj4+npCQEAl9cFZVMWjQIPbt20ejRo1kWkxl\nZaXMWfv111+lr+/y5cts2bKFb7/9VvoPAW655RaJ0hcLQM6jR2nJpfs2clCpqqoKh8PBsmXL6NSp\nk9RK7HY7u3fvltqmwJFpmkZ4eDgffvgh06dPl8nHe/fuJTs7WwpZoYHdcccdBAYGYrFY6NSpkxQm\ndrtdwgtE4rF4R5vNRk5ODpcvX8blcrFl61Z++uknNE1jwoQJ8t1Fyk9AQAC1a9eWyPzExERGjRpF\naGgoiYmJFBYWAlBaWip5bf/+/TLlKCUlhZUrV8qcRCFEgoKCGDFiBJqmERsbK31lIinfarVK6Eaf\n3r1lL0w1CCU2B39s1b+b73dDCKrfIo/HIwviCUyR2+0mODhYDrYQIpWVlaSnp+PypiV4PB5iYmJo\n2LCh1FbEghGTIvKi5s+fLyfV4/EwZMgQwNBWjh07xn333UdRUZFcVOPGjSM7O5t+/foRFRVFVJ06\nmM1mxo4dayRMBwYSGBiIyWyWOXsxMTG0b99e7qaRkZESF6Uu2H79+tGgQQPq1KmDzWYjIcHwULhc\nLho1asT58+d9GO/bb7+lSZMmBAcHU1RUxPz58+XYAZw5c4Z169bh8ja1ePHFF+W4CabOzMxkx44d\nJCQkEBISYuDLQOZQ7tu3j65du0ohmJqayrhx4+jbty9VVVUyyVateKFqlWqKhn8XFxEJE1TpdLJm\nzRoSEhIoKiqS72jSNDp16mQkUf/0E0nedJ527dqxceNGJk+eTGhoqEyVmTlzJgMGDKB27dokJydz\n5swZwBDWTqeTwMBAVq9eLUPxERERMjKpaRoerzn2/vvvs3jxYsrLy7njjjuM1COnkw4dOmA2m1m3\nbp2cU2Eig5GbKQT13r17adWqldyE1I1YjF/Lli3p1auXfMehQ4deV/lA13UOHz4MGBq2R9dJSEzk\n4MGDko/E+O/atUsK3MrKyuui5f4o/n+XbghB5R8iFVJf1bQqKirweDxcuHCB3NxcKux2HA4HQUFB\nclfZuHEjZrMZR2WlXBx79uyRpox/QwIV8yRMs4qKCsnUok6V2+1m5cqVcmIvXrzITTfdRO3atbHb\n7aSmpkr12ePxSOS7yWTC6k3hEH4NwRSiaqT4TvGtderUkUXWYmJipN+iSZMmxMTEkJOTg67rlJSU\nABATE0NlZSWff/45gYGBLPQCF8UiiIuLo1evXmiaRmBgIKNGjZKaozBjWrduTUpKCk2bNsVqtTJ7\n9mzA0G4OHTrEkCFDfHIdCwsLOXjwIFVVVTidTrk4v/32Wzp37izHSUVAi+/Ozs5mx44d8h2FP8/j\n8aBjwDWmTZuGrhtF5gSw1Wazyc3EZrNJX5SmaWRmZmIymfjyyy/lQv3zn//M5s2badCgAT179pTv\neNiL8j558iQ9evSQ75WUlMSlS5fYs2eP8f5enhoxYgSvvfYaM2fOZPXq1QQGBnI1L4/AwEDsdjsB\nAQFyMyktLeXatWsUFRVJfgVDWzt9+jTz5s1j8eLF3HXXXQAyIdlut5Odnc2FCxeAarhOZmamDG64\n3W7q1KlDkyZNCAoKIjU1leh69YiLi+PAgQOS/3JycgCI8xYvvHjxok9deVU4+UfJ/x3z74YQVILE\nIAmfFSAxRyLdISkpiaioKAIDA7HZbLKagt1uZ+DAgYa5o9RH37dvH3fffTdQ7RgVZpx4nsiI13UD\n9Xz16lV5vtOb1zV79mxphnz//fcMHTpUMr8waZYuXSrVaMkY+DanEIvdH1ejfrtQ+auqqqQTuLS0\nVPri/P1rdrudYcOGYbVaZWRImLxlZWVcu3ZNYmnq1KmDw+EgMDDQYFaMBZOUlESbNm2Mxq7ea10u\nF40bN6Z+/fpUVVVJLSYyMpLmzZuTmJhIcHCwT72kuLi46wqwqZ1kBApbjIHahBVdJyQ0FLfbLc07\nYZpdvXqVTz75hIqKCtq1ayfHfuXKlXg8Hj766CMOHjwoi9jNnTuXu+++m5KSEj744AMmT54MGCH+\nffv2kZqaSlJSko9vc8qUKbRt25Y5c+age4x6UxcvXqR9+/asX7+eUaNG4XK5aH7TTdIkVDtmx8bG\nEhYWxjZvUTwxLtOmTaNZs2Z8/fXXzJkzR2qgPXr0kPCZxo0by0oRYPhk1v/KKAAAIABJREFU33nn\nHZo3b47JbMZisXDXXXdhsVi488472bhxI1fz8sjOzqazF9MVFxcncxpDQ0J48sknqVu3riysJ0jw\nmArhEfT/BEeladpc4EXgNV3XH1WOLwCmAhHAT8D9utLaXdO0AOBV4B4gANgCPKD/D7d2F+TTK07Z\nnS0Wiw+wUCx+MFR3EQ4+evQom86elRUChC9m+/btMo8qMzOTTz/9lOkYhfMKCwt59NFHZblc9u5l\n9+7dFBUV0bdvX5555hmmTp0KwPjx4zl16hS7du0yUlG8msF9990ntTYJsVCcxf6RMLvdTmBgoE89\nJQFGdTgcfPPNN+i6zgLgxx9/lJUjRMKxOD8qKorCwkJKSkpYvHgx0zG0PlGMrW7dulji46XQfPHF\nF3nsscekz81eUSFTYsaNGycjjSUlJdSpU4eqqiofh2xAQABlZWUEBgZKnw4gy8ComrGYOxFkiI6O\nJrlXLzhxwqdcsCBN02S4XdTCAkhMSmLCzTfLQnitWrWCAwcYM2aM1GxVjbmiogKTyUSrVq1o1KiR\nfMfnnnsOs9ksK2u0bNlSjqPQcgVEIigwkISEBCIjI2nTpo2sVtCla1fOeN/5zjvvrNYoT53CnJbG\nDLcb87Jl8ptGPPYYOjDS5cLy3XcS2PvOV1+hb95c/e1e1PjIOXPQgLmahv7MM5idTkxVVYyeO9e4\nn/f8wNJSAtq25aoXhiBKWIPX/+fdHAYNGuTTmMO/WoKKSfy/Lqg0TesATAeO+B1/EpgJjAcygD8D\nWzRNa6brutN72mvA7cAwoAR4G1gPdP+j7/OPSDCripj1T5wUTO1yuYiNjSUkIwMqKuQgq/Wehw8f\nThtvIjJUh1979eol/VeDBw82JuuHH/jYZkOLicH10Ud0rarC6t0JHz58mNnJyXgOHOCR5GT07783\n7rN6Nb2AkRUVWJ1O6u3cicntZsCnnxoP9DJBZE4O12JifEw8QcJxW1VVxezZs312PLfbLc00q9UK\nP/0kzQUBbhTnP/bYY5SXl2Oz2Zg7dy7B5eXw+ON06dIFXde59957cTgc3NK8OdqZM4SFhfHKK6/4\nCJLuJ05QeuWKIUg1Tb7/sM2bZZTudl3H5HVUv15aiv7ZZ/I7BHX54AM05Zj4339zEQES9Txh+rXY\nsoUWW7bwEMDf/y7v3faTT3B6S/poQA/vtQ88+GCNPDXD2+3an8Z5q73+q+fX1E+y25tv0q2Gc48N\nGya7Dck58v4uMg98BIG/sFDupRsHff6umsli7HqsWkVLrxNepTHPPFPj96j+Ln8z79/BUf2hXD9N\n00KBg8D9wLPAr0Kj0jTtEvBXXdeXeH+vBVwBJui6vtb7ex4wStf1z73nNAVOAbfouv5LDc/7t3L9\nVq5cKStxqlqSpmlYKiqY8eSTv/uev4fSvK2uAIPJzL4dawXDaMIkFfa8X7RSpsB4/9c0jSa/XDdc\n/+vobKdO8v2FOQhcX2zP67uRkbsa/BmSX73jmLJnz+96lx+mTuW8931ERDGwtJTOn31mjDu+wnHn\n1Kk+Gqu4Tixm/8Xob2ZDdXKw6vxX0eTiu4RGr26qQtP3j1aLd48/eZLAkhJfDUYZX3XcBN/p6ibt\ndez38abV/Lu0SrmPCqwW7242mxk3bhzwfyfX723gS13Xv9c07VnlxRoCMcB34piu6yWapu0DOgNr\ngfbe56rnnNE07aL3nP/4ylNxNuCLryE4mDdef93H2S4YQe1n5/F4sNlsPvWWhMaidirWNM2nHK3w\nSwnns4A6iPw1oe6rWoyIDglzyV8LFOfous53Eydepzn444sEkFVohKIJpYBMiOeL42rZEvEs8G36\n6e9ANZvNBF67Vp2p710QqtpvMplkfp/ZYkH3VLcBF8/ov3Qp9bzZ+v8O/c2r1QkBIISFrusEXrsm\nny/8er8MG+aTAqVpGm2//JKpSled/61U7q0SqyodIcXFVERESOGrHi9XAgW6rmN2uXBZLKz0ls4W\nvN538WIKY2PZ7y3EJ6LH06ZP5/PFiynywneEcJ00ebLPOlJ51t818XvpdwsqTdNGAW0wBI4/xWAI\n9Ct+x694/wYQDTh1XS/5B+f8R0kVAP6CSAgjIWiE/0eNXojFJMKw4hz1Z+E8FAveP9omhI94n9Ev\nvFC94ykTK0j9vaa/iXfzHrhe+1COaRglR4JLSwn0+tP+N9P6F16Q3+hyu9E9Hka/8AKfzZ8vnbNV\nVVVYbTZGzZ/PZ/Png6bh9m4MsWlpjH788f/Iu6xbsABnVRX2igoZYBnx/PMse/99TCYT+/bto127\ndjJ1ad2CBT4LNNBuZ9DChfzp+efRNI24uDiqqqro+PXXxKelsf6RR7h8+TLh4eGEh4cz/tFH+X74\ncC7feqvPxjRl6lQmTZxI06ZNiYqKksJ9ytSp/O2VV1i9ejWjRo3CYrFw8OBB3n3vPVYvXOjD0wsX\nLuR8cTEb3nwTj8fDunXrDNzghQv0f+89Xn31VR566CG58Wbn5BCekCD9Ut99950EyHp0nVdeeYW5\nc+dSUFDgAxxV/1dJ1Sp/L/0uQaVpWjyGf6mvrutV/+z8/zTNnj3bJ6cIjC4ho0eP/ofX1YS3ERMY\nWFrK9N+wt8tq1eK8tyeesP9NJhPf3XWXjwBzOp3c/f77JHqrRf6rtMubo5eZmSl76d362WfsHD4c\nzWTC7XJRWFRErYsX6Z2ezk/e89F1fvr5ZyZWVOCKiuJ8q1bouk55eTm1IyPp8sknfN66NXVTU9F1\nnYKCAkrLyhi3bx9L33lHOpQ3bNjAuHHjmDJ1KvfPmMGZM2cYOHCgdKQ/OHMm77z9Nm63m/379xMS\nEkKYw8GilStZ+s47PuN785dfUv/MGTY/8YQUrIWFhTy8YAE/3XsvFzp0QNd1tm3bRkxMDG+8+SYf\neFH/4eHhVFZWsmbNGnbt3s3Bigq5OBwOB0ePHmU0UOhNp3G73cybN48FCxYAUOTNv9N1nd27dzOs\nVi1cFgsfvv02FouF559/ngULFtBn8WKK4uLYN2IEJpOJX3/9lbS0NLZu28bfX3qJ4shIucBCQkIY\nO24c+XXrUlBQQHpOjtHp55dfpLO5tLSUHTt20KBBA7kZfn76NA0aNKBRo0ZGVHjzZgZh5NGVlpZS\nVlZGWloaHb0ap9VqpXnz5jz//PM8/fTTuFwuArxara4bqH5x761bt9KgQQPS09MpKyujqKiIKRhY\ntry8PL755hufMsXLly+nb9++JCUlcf78eYYPHw6LFvHJJ5+wf/9+Zs2aJaOqbreba9eusWnTJqKj\noyksLKR+SQmZR46wOzaW1q1b065dOz777DOmAae9mQgnT56krKxMBg2E9aFq97qus3fvXn7xuinW\nrl0L4JM29M/o92pUNwN1gUNa9RZvBm7VNG0mkIqxpqPx1aqigV+9P18GbJqm1fLTqqK9f/tNWrJk\nyR/yUamkaimqg3nJq69K7Wrz5s08cu0aA86fJ8jr2xLnp5w6Rctdu2q897C776aoqIjs7GyGDx9O\nvXr1eGTWLNkaXtd1Tp48SUxMDH+aP5/D3uJ17586xaTOnQkJCeHWzz5j4oEDEhPTt29f6jud9MzI\n4Gj37tI38e6+fQyvU4cf8/P5NS6OtLQ0cnNzuW/wYLp88gk/NGiAKSaGsLAwgoKCWLNmDeMwivJ3\n6dIFi8VCSUmJzAvbuXMn+fn5EvAq2kWpJm1cXByHt20DkCar1B70akgAGMI3NzcXgJLiYtauXYvV\namXv3r3ccsstAKxbt46rV68yfvx4fvzxR06cOCHvceXKFVq3bi27+uB16FZVVbF27Vrmzp3LK6+8\nwgNUgzxdLhc5OTnUatsWl8tFWlqaxKCJIAEYm9SuXbs4duyYsclt24bD4ZCwkpKSEokX+tvf/sa5\nc+cYM2aMRKuDEXQoKSnB7XYTEREhoQLdu3cnMzNTmpouL4+Fh4cTERFBkyZNSE1NRV+/HjSNH374\nwYB3aBqrV69mSFUVx44fZ82vvzJjxgw0TZN5l/369SMnJ4dGjRqRkpJiCPPVq3G73XTt2pX27dsT\nHBzM4sWLAahXrx4NGzbEarWyYsUKCdYdPXo0R44cIT4+3igj4xVsqampNGzYkJYtW1JRUUHYrl3E\ntWhBzk03YbFYCAwMNPhi2zaysrK4du0ae/fuRdM02eRWdcoL3rBarXTu3JkuXbqgaZpsL6f4qP4p\n/V5BtR1o6XdsJYYjfKGu6+mapl0G+gBHQTrTO2H4tcBwwru856jO9ATg93lG/0USppjqBFWbkUK1\nn0VqWoGBFNSrx+ZJk2Q1yA0bNvCN1cr6O+6gaMAAH0Tuw488Qr9+/Vi0aBGJiYmSOR7BKNxXXl7O\ntGnT2LhxI/O81RpOnDghw+9btmyRyboTJkyQ+WxpaWm4L16UYFGbzcbf/vY3iouLuex20+rmm3l2\nwwZZalagu7t160a+t2Ll2rVr6dChA5w8SZ8+fXA4HKxbt4709HQivdUwk5KSCAsLw2KxMHDgQLnb\nHTx4EI/Hw9WrV8nPzyc1KQl27waqtVJVnRdmxo4dO7j//vthwwZCQ0O5u2dPTnu1jV1eQT9ixAhZ\np10COTds4ODBg1y9epXMzEwKCwvZvHkzU7zP+/7772nevDlhYWG88MILMHYs27dvp2PHjlLbFg7o\ngwcP0rp1a5nS4lFSmOrWrcvYsWMl4LO8vByr1x0QHBwscx0nTZok8z8vXrwoISrp6ekyT/LLL7/k\n0qVL3I9RS7x169a43W42b96MzTuOIon5l19+MdwOv/5K/ZAQ+vTpQ2hoKC+99BKjR48mcO9eWrVs\nSfDNN8u2YCLNaejQoXz99dc+TT7BSKhu3Lgxv/76K6dPnzbKHx85gtPp5OTJk1RUVNCqVSsJxfj6\n669xOBysX7+e9PR0/tqzJx6Ph9q1a7N//37Wrl1LrVq16GmzceXKFY4ePUpCQgI5OTkcPnyYhzBa\nfYWmpZGYmOgT4RXjr5JarfSPNiH9XYJK1/VywKekpKZp5UCBruunvIdeA57RNO0cBjzhBSAb+MJ7\njxJN05YDr2qaVgiUAm8AP9UU8ftPkBp9UQdKXWBquVaz2Uxubi71S0pYuHAhDz/8MEFBQUatngMH\nyLx4kS8//hi32y1D9w9TXYGgrKyMoKAgQ/AcOcL48eNZsWIFuq4TEBAgfVUNGzbEZrOxb98+2Y0Z\nDGZv164dw4cPp7CwkKCLFwGjkkHv3r0ZM2YMH374IeEFBZw4exZnVRUWi4X58+fTrVs3HgDeffdd\nWg0ZIjvtim8VFRj69u3Lnj17jFrd331HZWUlwcHBsuaQAHy2bt2akydPUr9+fcrLy6UwVQWUiB6J\n8Ttz5gydO3eWAFYwmHXVqlVMmDBBHl+7di1NmjShTZs2rF+/Xmq4x48fZ8iQIXTt2pUTJ07w1Vdf\nAYYGlpiYyOXLl8nPzzcKx4GsZ++/EEaNGoXdbq+ufgGyM3azZs1wu91kZ2cDhsZT4uUPXdclsPP0\n6dMS8OhwOKT50rx5c06cOEHTpk255557jCYRJ05w9913U1paKgGUoXY77NlDv379KC8vJzk5md27\nd9O8RQtcZ8/KWuxXrlxhz5493ONycf78edacPk337t1p2LAhq1at4nHgvffeM3oTnjuHruskJycz\nGUPgnzhxgm7dutGxY0fWrVsHGJtVvXr1KC0tNXr0eXMs+/fvT3p6OoMHDzbcF17MWbdu3UhLS2PQ\noEEsWrQIPSiIzMxMOkydSnBwMPHx8QZY99Ahzp07R15eHpGRkbRs2dIntUmtFCLIf+39XvpPINP9\nIsz6IuBN4D1gHxAE3K5gqABmA5uBdcAO4BIGpup/hMSiUp3gIsXDX6sSlRPr1q1LnagonnvuOTnB\nOTk5VFZWclOzZowYMYLhw4fTtGlT6SPLzs4mJCSEvLw8MjIyZAeXDRs2SJBfZWWl3IkPHz7M4cOH\nCQkJkRFEMJJMu3XrRkxMDN999x3FJSWYzWZ69OghF0taWhoOh4N69epxyy230KdPH5o0aUKPHj0A\naNq0KdHR0URHR3PvvfdKLWb16tWUl5fzyy+/EBcXJxee6OArsGSCqVauXEnr1q1p0qQJR48elaaM\nEOwiICFMPyHoVWS+25v2M3v2bJo3by5bLo0aNYoWLVqg6zojR46U6O5GjRqxf/9+nn/+eTZs2CDn\nqEOHDlgsFurUqUOtWrWkMN2xY4dEwotUHLfbzeXLlykvLycmJqa6USqG2eZyuTh+/DjveWtWiUiX\nrhvNRMXxhg0b8vXXX7Nlyxa2b9/O0aNHAWOTy83NJSgoiBUrVkiz1Ww2SzPXZDKxzAvMNHvzMg8f\nPkx+fj6BgYFYrVZatGhB69atqVOnDt26dcNisdC4SRNGjRpFSkoKn332mTSrhg8fTrdu3ejZsycj\nRoyQbpCKigrOnj3LsmXLyM/Pl4DauLg4dF2nVq1aMidPvEv//v05e/asRO+73W6WLVvGiRMnCAkJ\nYeHChdSPjyc+Ph6bzSbTcQSwNTo6muTkZOLj43n66ad91pHqXhFjJX7/I3Ao+A8IKl3Xe+sKKt17\n7E+6rsfpuh6s6/oAXUGle/9eqev6Q7quR+m6Hqbr+gj9/xIq/R+RGEh1oAWU4dq1a1y6dImAgACf\nUitq8f34+HgGDBhA9+7dycrKkukGgwcPlg0tbTabTGXo168fYWFhEuGuK4vd6XSSmZlJ9+7dZaOE\nw4cPYzabCQ4OpmXLloSGhlK7dm0iIiJo1KgRd9xxhzQTAgMDpbN/7dq1ErsyZMgQgoODJfJbJE6f\nPn2ahIQEbr31VtmsAozyIIGBgbLvXy3vIlCxQSaTSe5W4vv2798vHakOh4Pvv/+eCxcu8OOPP3Lp\n0iUAdu/ezaeffsquXbvYvXs3r7/+OmDUqerduzdRUVHcd999cj6SvGk4hYWFFBcXywU51Yt1EjmG\nH330EWazmdjYWNasWUNoaKhs4io2qtzcXD777DOe9GLoxEJ2u91ERUUZZivGoh46dCiDBg1iyJAh\nRlYBRgPW8vJyrl27xsSJE2UHobfffpvi4mLKyso4duyY9MfZbDY2e1Hi99xzj8Qyud1ujhw5Qo8e\nPaTZLjbMiooKhgwZIr9TQEnE/YRmmpeXx0033cSkSZOIioqSZrsQLiIdR2yEf/nLX2jcuDGff/45\nW7ZswezFbz344IM0b96ckJAQzp07R1paGtHR0VLQLFmyRJrXycnJuFwuQkNDmTNnjk9fP//ongpL\n+KNRvxsi10/FxoBvQ1JBAqsk0iQ8enWeUkhICJGRkdxyyy0+wDnRFVfQ4sWLOXr0KGazmZYtWzJ0\n6FAAWSJDaE1/9yKiS0tLZaJuUFCQFFQnTpzg5MmT7N27l/bt2xNVpw4ej0dqDq1atZK74OXcXDIz\nMzl69CgnT56UDuyAwEBee+01jh07xuTJk1m1ahVgRJ88Hg/33nsvdrtd+qiKiorYvXs3AwcOpGPH\njlL45uTk8Nprr3H8+HGGDRsmI20if1HFQImxrqqqok2bNnz//fdomkZwUBC9evWic+fO9OzZk+jo\naMBIiRkzZgxdu3alY8eOPKigwFNTUxk1ahQmk0nmrnk8HtnXrn379jIkfvLkSel76ty5M2PHjsXj\n8fDcc88xZMgQRowYIXvQ4TW/v/rqK0pLS40WUhiCWmQVeDweWS7nwoULLF26lE8++YRVq1bJMjN7\n9uxhzpw5pKamMnfuXL744gv5Tc2aNcPj8Rjtxbz5i5s3b2bGjBl06tTJ0Fa9QvzQoUPk5+fTyltz\nTNeNXoiSDxV/zzfffMPZs2c5evQo33zzDd97Mxk6eQGsP/74I4sXLzYK7WEIzY0bN6JpRu9EsQ7+\n9Kc/8dZbbzF//nyio6Nxen2tRUVF0upo3rw5jRs3psKb/2mz2Zg1axb9+vUDDGsgMTGR9evX8+23\n30p3hrBW1Hw/sYEInvkjdENU+BQMoKKJ1TpHYLTuFiUyrl69SuG1a9i9msDZs2e57777pDBzu91k\nZGTgdrux2+2SmR566CG+/PJLfvnlFx599FGWLFnCYxiNIHv27EmHDh3o3r27sfvu3InJZOLzzz/n\nzJkz0q8BRtrKyZMnuXTpEsuWLaOv0gYpPz+f/fv3c+bMGWyxscTExJDSsCH16tWjfv360mRLaNCA\n+++/nzNnzrB06VIef/xxePBBfv75Z2JjY6moqJAMDDBjxgzZiishIYGePXsC8MQTT0ign6ZpTJ8+\nHf7yF9nIQiZEe8dROLJFNQbPpk1y8QPSpwf4mN6qhhAREUFlZSW1atUiNzdXOrbNZjNlZWXExcUB\nSNOvvLxcLpTw8HB+3LKFW00mFi5ciNPppLKykvnz52NevNhAYns83H///dX1q+67j3bt2lHoBee6\nXC5Z66l+/fpMmzZNBk4CAgJg6lRatGiByWSibdu2RqAC4Pvvady4Mc2aNSMoKIhz586R6O1VOGnS\nJFlWxe12y6YWrVq1Ijw8nIqKCkNLpXpDFSDdVq1aAXDbbbdJPJ4sKPj113g8Hmnyd+zYUV7/hBcq\n4nK56N69uzTbej73HH0sFjzPP09fiwVraSkml4vpH39sVIzdvh1N06idnU24zUZDbxkjFTw679gx\nPFar0WHZZKLqjTfknIq1JbRtEcxSy+/8XrohBJVaHAyqs7vVsiixsbGyamWrVq1o+tVXBKel0adP\nH1muQ6q1mtH/79dff+XWW2/10djuuOMODh06xKFDh3jggQfgiSeYN28e+fn5BAQE0K1bN6niA4wc\nOZKLFy/K9Alxn+bNm9O2bVvsdjtJJ05gPn2aGTNmYDKZuO2222jTpg0Bn31GrYwMJphMWC9dwuz1\nnwCEhYWh16lD3bp16dOnjxQUY8aMkQJ63LhxsshacHAwTqeTp59+WmqWUA3jEO8W5A2VCw1QrVEk\n3l3U3YqIiDB8g0pFB5GYzI8/VgsK8KnYMLeyEv3bb2X+2mCvdtdu82baejxw4QJcuCDf6X0lQVel\niZMmXXfMZrfT9ssvQQH9Aoz4jTSq38r1e/a552o83mPHDikMW3k8BHnH/bdy/R5+5JHrjvVbvpx+\ny5dfd/y+GTNqvMdv3XuS1+enUkbLlhQlJ0vTUwiaDO8mLjsDAbmpqfI8lM0oNzVV+iJREOi53nJH\nLpdL+glVM/CP+qfgBunrJ6oXqDXFhVZlKStjxlNP1XhdXlwcPwyr9vGbTCYGvfceB3v0IKdpUznJ\nbrebkW+++Uc+7d+mXG/bJl2vzgU0u1zU80YK/79IuSkpNR7XtOrqneKbDw8YQKYXbCg2EjWCK4Sp\n0KQHvvyycTneBqHee2564gmg2h2gbj5qJoP/ohOYIV3XGSI0D5V0nR0TJ1JSr951fhtxnb9LQv1e\nn5JEfk5qtYqG6qPzf46a1eCfuK7insT5IpiibuTq/dTr1RQaTdNqjO6pyc5ms5lJ3g3k9+T63RCC\navny5RQVFV3XMVYVXP5Jpp6qKh71Mu+/Sm94e/KJiZNRDm80SUyYYHqhwovzVNVYZU6VkdUyLup7\n+wcCVBJM7E/iGsGQ4nqV4cTirMkJqp4vxlXtracuRLHo/PMn1cXi/zd1EagOWTXoIN5NjKM//ER8\nh3pf/7FUSZgo6rv7+zRrWjPq9/oLippI/Sb/6LM6h+r8q3Pub0ap91Kfr2ZjQHXtLpWPXAosQ/he\nhYbvz0/+dafE//5BKPXZQiMX5/8RQXVDmH7qwKkCSTDW0Pffl+eKwY5QaqH/q/Swty75f+nfo4vN\nm19fyUBX8hm9P+u6zrHevclu3txnQQmBpS5SNTQutGk1GKAKChV1D76FFtVzVcGlRkH9N72aSAhl\nsfBVQe1/fU0J4Or7qPysVphVzxHf7X8v9RrxrJrGS32Wup5qep5qtaibjTAJ/wjdEIJKHVxVA9B1\nncCyMhqePs2BHj2kHa5j+DLKw8L4+8yZ8jqXy8XMP/2JH4YPJ61tWx9t45FZs3h18WKJ1xJM98is\nWby2ZInPs8HwTSx+5RVZuUDQgzNnyvMDAwNxOp0knzrFbR98wLtLlvgsrEFLl1IYE8P/Ye+9w6yq\nrv//17llOkyhDL06Q1GaAgoKBlEQK2JsHw1RY2LX+NEgRMVeEmMvGE0iKkFFbBARUCkjJaCAlKH3\nIgPD9Hbvnbn3/P64d+1Zd3NRIfnk+3sesp9nnpk5Z5/d93u919pr7714zJg4yXz7HXcweeJEKmNn\nrQtA3/nb35qTIqSMruvy27vu4uWXXjpsdfSOO+/kheefj1uA8JaWcuMDD/DSiy/GTfbTPv+cNps2\nMfN3vyMQCOD3+/H5fFzz29+y5Oqr2dS3b9wkvvmWW3jj9dcPO9P91ttu41BuLknqEk+Px0OfL79k\n9TnngNt4IQfABS+/zJIxYxqZWez3mti1XfbESsROJEg/yE4EaGTHenOvbeu0mSUkPpJX+k0EpGaz\nNsOzAdauSyL2LO/lVFC7LD80NxIxOimTnXci8Jf4UicN3jawHks4LoAqUSdLkK4uiB10J4N50OzZ\ntN+61dBW7RDoui6hUIhQKERycnIcBZZB4vf7jU+TpGvbILZv30737t3NoBJpEw6HOXjwIC1btsTn\n87Ft+3YgXlKZAayea7VDHFdlsMk+tfLycnPRgG6LzZs307Vr17hjfSHqJX/xxRfj9/uZP38+J8Vc\nC8RTu6Kigvr6empqaqivr+eRRx5hwoQJBtgdx2Hu3Llkd+lCZmZmXBlF/X333Xe57LLLmD9/PrcC\nf2jenJ07dxoVIRgM0ufLL1k6Zkzc6awej4d+X31F3jff6M4mKRBgwIwZvPHii3HsR6s00uY2OxJH\nYGlDETi23UWvbEkaslVErzLr71w3/uYceSd1EsahwUyrqyIEpe42CEvQ/lOSl7AprcrqoAFc8rfV\nc1utlff6CCFdH6mfLKL8EMP8sXBcABUQ17lagumJumvXLnP8bbvEUaF7AAAgAElEQVQ9e2hSXs7c\nuXPZtm0bt9xyizlm2I3F37lzJzk5OeYSS4gOku+++44lS5Zwp7Wi4ziO8UqH6PVH4i1cV1dnBkFt\nbS3Lly+nZ8+e9OjRg1WrV+O6Lm+++SbXXXcdPp8vWg+Vrg08H3/8Madfc41x9JPLGqZMmcLtt99+\nmOG1pqYGx3EIBAKkpaUZB77KysroJZWDBrF8+XIC6qZgiG5ryc/PZ2hdHYcOHeJXd9/N7t27aRe7\nChwwF6l+8MEHZGZmsnLlSm4ieoXTKaecwuDBg1m9erVxlQiHwxw6dMiAt0yCdevWGR8lXdfpEybE\nMYxOhYWc8+c/x00wDRp6n5xtA9IGbBFS2v5lMxzdt/a5ZPYE14BjmyG0EdpWNTXDkQ3YtjqnnZC1\nbUm3leyMsG2Ouj6aQQkoSvp2nSRoxmS2K6nyCQhrdfpow3Hh8CmN9UON1LlzZ0aMGMGQIUNo06YN\npWVlZGZmcskll3DjjTfS0NDArFmzCIfDFCxcSEFBAaNGjWL9+vWGgcgO/b59+3L99debPVcaFDt2\n7Gg2wubm5rJp0yaWL1/OqaeeanaSL1myhA0bNrB+/Xoef/xxc7/gZZdd1ug/Q/xJn/bE6dSpEx98\n8AEFBQVUVFQYoLryyiuNs2hycjJPPPGESeOjjz5i586dBlgA+vXrR//+/fnuu++46KKLjM+Q40RX\n1wKBAMXFxeY2nCZNmlBYWMiyZcvMAYKh+np2797NiBEjGDlyZFzaixcvpqysjA0bNrAzdmDe2rVr\nqa2t5a233iIQCJhBL7ehSLAncyLwSNT39jjQYKbVMsdxDBuQfpQJHMdqre9tdiLf2hNcl11PcDuO\nVrU0q9L2rUR1kZCIcSdiVaKuQfwlGdrxVIOQrQrCkW9FFnA+VofP4wKogB8FquTkZHMzS0pKCrWx\n89KFzvv9fkaPHo3P5yM5JYXKykomTZpEixYteCnmmiBMx+/3s27dOnNUiEhMkWTi9X3CCScwYMAA\n41clg+iiiy4ym3VPPPFEc8LAp59+SnLsXG/XdRuX6lWQwdO1a1dat27Nzp07WbRoUXTTLFFVTsry\n9ddfc9555wFR9erSSy9l8+bNvPnmm2bArlq1iq1bt7Jv3z68Xq/xBl+7di0NDQ2kp6fTs2dP6urq\n8Pl8FBUVmeNIBLiTk5IoLCykuLg4biJGIhHjVb17927j9Txs2DC6dOlCjx49zJ45gLPOOostW7Y0\nMlvLrqJBQ57ZP7qN5G8BGBECMhm1SqZVOm2XkvjyYy/1J7JLHcnWY4OVAIutSto+gJqBSbsK6GiT\nglY3dTtopqRZpwZdDY6SvjZn2IBsL25IGROttP6UcNwAlS39bPounSJAkpaWRtH+/TzzzDNmM2Yw\ndp9fZtOmZGZmkpuby5gxY4yntV71Wbx4MdfGLqvUtoeSkhKzgTUjI4O6ujq6devGjBkzjOpTWFjI\nxo0badWqFWPGjGHUqFF4PB727Nljls4bGhqM8V8vL0uYMXOmuRJdOzYmJyeTEbsyqqioyOxdq6ur\no66ujqKiInPhpZS9W7dudOvWjWAwyKzPPwcgLy+PhoYGioqKWLRoET6/n5rqatatW8cHH3xA69at\n8XiihwqWlpZy7rnn0rlzZ6BR6uptRbfccovZjxcKhdi+fTtDhgyJmwzCbmR5XhvbNZuxJ4/0rz7N\nVb/X30v5bKGmwdFeNdM2Ha0i2oxOwE4vWuh8bVcCm+VpNwvbz0mrczbTkrJLG0hcKbN2kdHqqS6L\nxJV87ZVJbaeVoAXEDzG5nxKOC6DSYGRLNFsqm46LRGjXvj3Dhw83Wx+ef/55XNelrKyM77//ng0b\nNvDhhx9y4ED0jEA5SeDLL7/k6quvjjMwyqSKRCLm9ICvv/6a+fPn07RpU7xer9l8Kob0PXv28Oc/\n/5nPPvuMcDhMSUmJkapz5syJ1ieWvvaNAdi3dy/l5eU0b96cc845x6hbl156KVVVVWzcuJExY8YY\nD/QWLVrwzDPPMHToUIYOHWrSKSsr47PPPiMpKYn58+dz2c9/btrKcaKH6Z111lkE6upo0rQp559/\nPiNHjjQMNTk5mVatWhEIBIwBW9haOBxmxYoVfPLJJ2RkZJgD4mS/oLYJQfR6eTnrS86NgqhDrzY+\n25di6P611URtt9RqnR1fs5pE40gLCg2oicaipCu2skRs0I4vpy/oPGQ8HYnVJWJuGny8Xm/cMTh6\nBdLebaDBXUBTxrtmoLrdNfjZDPhow3EBVBDvGAmNZ+XYlDUSiZjNqeFwmD59+hiVbty4cfh8PgYN\nGsQjjzxC69atKSkp4fHHHzf57N+/3xwtIkzr+eefp6KiAo/Hg9/vN4bqn/3sZwwaNMgMDgGN008/\nneTkZPLz8/nNb37Deeedh8/rJScnh4aGBurq6liwYEF0b5zbuMQtklPqt3jxYvLy8pg6dao5sSAS\nid4G3bdvX1zXNWWcP38+N954I127diUUCpky5ufnc8UVV5CamsqgQYPMSqak1bdvX1JSUgiGQgQC\nAXbu3MnevXvjmIWE9PR0gsGgUUUikQhDhw4lIyPDTDyA0047zVxZrgf4pZdeSkpKiplw+gwkcYfQ\nR87oiaTbyFXvpc81GOmJbhuP7cmmmYceX7JIopm7ZiDyra22JbJhSVxtNNc2JFuF0/lqFVLGvIxt\nnZ58o+sidRMDvg3Q0uaSZiL1zrbZHWs4LoBKS0GIp9S2kdXYKyKNXs8yANesWWPUgvfff5/LLruM\n0aNH88or0cNLv//+e1auXMmFF14YN8FuvPFG3n77bQ4ePBh3YWmnTp3o0qULdXV1HDx40MRftGgR\nDQ0NLF26lFmzZrFixQrCMSCT8p522mmkpaUZRiXSWwbjyJEjGTRokLGD5efnA9HzpaqrqykuLqag\noIC/xvaU3XLLLWRnZxvprW9ZDofDpKens3jxYj766CMgyuDmzZtnbvlt2rQpPp+P1q1bm9uM6+vr\ncYDqmhrS0tKor69n48aNtI6tHIpqKFfCC2iuX7+elJSUw1TaNm3axK3YCVBde+215oiWI0lt3T6a\nKdnjwgYmnaatHun4WkgIKGghqNMS1xH9TvedNtprNVNcLAS0NIMSRmOPcbuciQBTA5QNypKvVpsl\nL1uQ6G8E6GxD/7GqfseFe4JNq6WxdGdllJfjeDx4PR68VVV0zM7Gdd24K8H79OmDx+Nh5cqVXH79\n9YTDYQKBQPTAt3HjeDbmqEns+A0JD0ycyAMAsRU2CU0qKshwXUb378/69HTSYxuEf5aXx7C8PDNY\nO2zdimfVKsaNG2fsXRdffDGev/wl6gAZOdznpn379uS2bUtSUhL5+fnk5eXBP/7BPffcw8GDB/H7\n/YwYMSIKmitXxk00zQwuv/xyQqEQqamp3HPPPfjKymD8eDweDxdccAH19fXce++9NPv0UzIPHCCr\npoYcx6FTly64VVXgurx44AAkuGjztttvB6K32Orw0ssvR/+48cbD2kszHZnYXq/XuFXYk1UzFq0W\naTXflvQykXW7imqtVR5xR9A/0naaAel09OSXMspvbR/S5bVtT9pdQsoi+WmWJvnoNtA3Gify99Is\nU7dFIlYk9dL+f9JWEtdmbLY/2k8Nx8Vev7/97W+UlJTEdaBp+EiEu/9NF5D+7d5746i6C9GtIG70\nMlFXMbjrY5tj/9UQSE2lLmbbkZBdXExFTg4Ra1Bk/8C2oLLmzRu3qPyE+EcTpjzwQNyE0AZvI+k9\nHtNWNsC4rstYpV7bobxly2gaRF02/KEQKTU1vBYTHHpC6i0cmpFIWaRs2uitWbX8L3Yc2zdPA4Dk\noY3rEjRjkzQlaL8laFws0WXV++c005NvRFXTq3g+n8+YFxyn8ZQL+V/Kq1VJe++kbXgXILTPztJp\n6vp6vV5+Hbsr8b97/awgg0Q8k+PeeTw886c/HSZVbdqsB4lNpeWZ9mLWur0WBjIQ/vT004dNnES2\nDrsO8reUp8+SJfKxsc0Yik68jcONRFgduwlEBnh9fT0nf/stTgLja0luLrs7d47LV6/6iFFb6qm/\nlbh6tU0Gunxn11dPNL0E7zgOzz/3nGEQ2r7Ya/HiqFQXVTMWf/2ZZ5oLUCVPaf84w7sTf62TBgLt\neS7lt90HNOjajEqbF3Rc25YEmLIfyX1AuwvYIG5rDKKK2mNIg5BtO9KqnV1m3Xc6XVv46LbQY8Ee\nx8cSjhugsv+3J6UdT0sYrVLZgKXT09JTOtk+QMym0lqlsNWHH+p8yW9V7KhbPfGkvDL45EfXWQ/O\n1TFfJl0vo155PIepGtoukyg9CVpaaxuRfRMzNDILiaevMdftqts9EomwLnblmDAcU1+rbJJuKBQy\niyOJ2luATY8J/VyDm24r3ba2L9WRJq8GBT0+NCDqfYf6W92fNnDa41P6xgZc20Zrl1PqLNuqpE8E\nUG2/Mw2iNkglenY04bgwpkuD25NEGlmkFRy+aVkbKvXKoAYuGRCyWihSRyaupstaaulyaJDU8fRg\nk+9sQNV56HrpstrAbLszyPK3vNd0Xqs+epVLt49dXl0vAWptR9FxZcVPf6vtZdpHRya0rpdmb7qN\ntEonQdw0NJvQPlIyCT0ejzF6i5ok8W21VQOGDdhSVz0mtC1K2t1mmPJedhFIO2iblbY/JVqZk7JI\n3vZ4T3TygRZsevuQ7TulBbC9yme3jT1OjiUcF4xKh0T2AnuHPBA3OACzmVX2SiVqcH2SqM3AdJ4/\npOLJN5L3D6lHEK9yStCgpdPREtsGLg2mdjpaJbFZgDxL5HRq1y1u+49qj0S2Q/t7PQETqdM2U7XL\nKPnolVOdnw04NlMSv64jrVolYhCahWmw1xNXCwz5LZvadT10v+tvNJPRl6xK0CuJdtm14BFhIXlJ\nvUW4JzorLVGfaduende/Eo4boErElOzlYM107A7Tg0VLFIi/v0yrLFpVkDzFpnP2nDnRD1x1RIjK\nBy3hPB4KYjcXa8Ow5K1puExkUf1kMtg+L/q3Zi9SZmg8s1uzIKmrVv9020r5te0iEbhpQBFpLS4N\nMjnEXSHaTG6c8VezKNsYLqzLVonskw2kDP7YkTI2OGlA0c67NjPW8WxBosHYZkN23TUY2x7kdnqa\nlen+0wxbCw4toGxmLEJGaxtiz9WMKhFDlfFj21ptjcFekDjacFwAlT0A9TMdbCYkk0NPPlvi2+xE\nMxwNhPJefg8sKGB7t26SkHneedMmdsTOnpY80mpquOPee3nmscfMaQh6W4wdbHuEgIl8p+svZZaB\nqutjMx2tYuh6QeNgT2TzSGQglvdaAGhw08xXf68nvgZQWZjQeYqao2+XkTQS2e+kDBqsbXUyOTk5\njn3olTBdV/lf6iZs3GY48l7bAaU9NVBru5Kuj5TVFra2ZqDHtg2wtgoJmLzFBUMLed0+egVU/reB\nTLflf1W/HwlaAkFioNJxNc3X+jjEszNJS1iWnmgAhEL4RLJFInhoHMTTr78+jt25rsvd99zDRzfc\nEFe2zuvXc/E775DiOFBfj6e+nqSkJIL19bgxNcHrukSUodujJrTHdSEYZPhnn3HKokUJ6/zkE08Y\nCapVVZHMWkLb1F/ayh6IPp/PeGhLfP23BghpO+15rW180kZ664gGKQ0gumxSLg3ANnDa6q58o8/0\nkqBXvTSzlrJpNTxRfZOTkwkGg4aNSp7C2Gy1VoJmpFoIRYdYKG4foWb6GmB03TWQ6rrarEsLLS2A\nxcAuJ21olm+zTL04cKx+VMcNUMHh2xmkE66eNCnOhygR9Y89AMeh/a5d/7byyG+RjtDoDa6pu6+h\ngTv/Df5e7916a1TFBOPnddWrr5pLTvXKDjQO7Lh2gMNUE2lTWVUTJifpyjuR0BCvXtsCREt/yVuW\n8KVcelImMvqKdNd9rSezZkTCEsXXSKvwtv1Lq20CpLbdSIK+707ATL7T7+Q73ZZardXqml2flJSU\nOMDRNitpbxug7PpoNp0ojs1uRZhrZq/bSfef7t8jaQE/Fo4KqBzHeRB40Hq80XXdnirOI8ANQBaw\nGLjZVTclO46TDDwLXAEkA3OAW9z/0E3JNrNKra6m3a5dLFLH3Pq8Xtpt3UpmSQmrTzkFF6IMxXE4\nbeFCPrnySracfLIZ0JFIhAm//z2PP/ZYnBQJh8Pcd//9PPXkk3Esze/3c8/vfmcGlhzdqweFDC5h\nCQ0+H8898QSu61JZWUnTpk25+LXXqGjXjsWXXGLKEg6HGXfvvTz561/j6do1TgL/btw49nftGsdk\n7NU1DR56wNl2Fw1g2iaVyCan1R9t0JfvtQFYA5NWZWxpL9/qSaiZqWYSGnh1HXR99VEoGkzt+knQ\nTMtxnDgmZE/2I5VBl0MDlM3UJYhRW6vIdrvpPpP2FlXRBlytLiZiy0eaM3o8aGZmx5FyJlrRPNpw\nLO4J64BcoFXs5wx54TjOvcBtRHdFDARqgDmO4ySp758HzgcuBYYCbYAPj6XwPzVoFUA/c93G87cX\nDx/OouHDWXrOOSwfNYp3v/+eqpwclo4YwbKRI/n6rLNYes451Pt8ZlAK/ZVjW4QSA+zevZvJkyeb\n/A4cOMCkSZNITU015UhLS2P58uV8+OGHlJaWmqVzn8/HSy+9RHl5eZxhuLa2lr179/Liiy/y/fff\ns3PnTirKy83k19Lq/fffp7S0lNdff/2wVSQd9KC1VY5Ek83jiS6Za7VYBr9tu5Dy2DamI01YW3pL\nSDQBdbnkb/1cwM12u5B8tNpoMxWtimpHzETAZ9vQ7DrpRZtEbasFmzzXJgYbmLU9T5icfmYLGG23\nk/T1XNCCwVZrNZBpoaPtYzbrhCMfEviftlE1uK57pL0VdwKPuq77DwDHccYCB4DRwDTHcZoC1wNX\nuq67MBbnOmCD4zgDXdddfgzl+dEgg8mWQK7baMsR1WTevHmEw2GGBwIUFRXx7rvv4vF4OPvss8nK\nysJxHKZMmcK0WJpPPfWUOZ7F7N4neqGpnDRw//33k52dTXl5Offccw8ej4dxRK8RnzlzJg0NDaxd\nu5YWLVpwJ9HjTBzHMSdkykCvq6uLAwzHE92m4/V62bFjBykpKXE+STt27OCkk05ixYoVDB48OK7u\n8ltPOHuQyt/6vUxsXVc9WIWdiN0kUT62dNUMSIAwOTk5bqJIsJ9pFU2nqcul1RbbaVPYkLahiM1I\nWJwNwnadpFyJglbJ9ES120QHG5jkma1+a3Czjem6/rbnuO5bWwDYxnltZLdVOls91e1zpHb5j6h+\nsZDnOM4+IAAsBSa4rrvHcZzORBnWVxLRdd1Kx3GWAYOAaUD/WJ46zibHcXbH4vyfAJU49CXariId\nL6xjyZIl3HHHHZweDtNs1y4uvPBC3n777TjD5Nhf/pKBvXvjOA6TJk1i//79TAKefPJJTjjhBPr0\n6cO0adPMUSkDBw4kHA4zevRoFi5cGN1vNX8+GzZs4NZbb6WgoID+/ftHrxGfMAGv10taWhrBYJDa\n2troiQyR6PEsBQUFZGVl8Y9//IOL/H4CMXeHvXv3xqlUmVlZ7N+/n9atW8ft1rcHmx60Wtraq156\nAy4cPuC06qGXuW1WpX3W7Hw1oOgBLuWxJbw9MXU+8k77ANnMUzMpe7uPxDuS6mvvv7MnpM2SbFZj\np2kHbXPTaci3krcIWHkmZdP2Q/uevkT2KgEjDWTC5sPhsLnq3m7rUChkzkLX4+ZI4T9lTP8ncC2w\nCWgNPAQUOI5zElGQcokyKB0OxN5BVGUMua5b+QNx/u1BOsg2TmoJpxvwo48+ol1JCU3q6pg8eTLF\nxcUEAgFz1vknH3/MhzNnAjB27NjoDS/vvMOIESMoKyujc+fO3H777UyaNAlKSuIMtNXV1WYil5WV\nMX36dCorK9mzZw9NmjRhPPEOfU2bNqVJ27a4a9aQk5NjJl1tbW2cWtG1a1dWrVpl/u/ZowffVVRw\n8skn/+Dg0XRdq0HyTKtIiRiYvRxtT2yZLCIobMdSbTfR+Wi2ptVIDVB2HgJMtiojeeuyaruJlFnb\n6/S2Fbu82rlV0td5CuOUNGX8aVZmp6vrLmlLeTSbsdU821dNA5S0DRB3PIy8/zEnXvleyinjWIOV\nnld6ZdBWA21mfLThqGxUruvOcV33Q9d117mu+wVwHpANXH7MJfgPBC0l9N/2/jHprNtuu43+AwbQ\nrm1bJkyYQJcuXeIGzuDBg2natCk333wzmZmZRsULh6OnTgYCAXNBAUSPHL766qupq6tj9OjRdOjQ\nAYDLLruMU089ldzcXDp27EiPHj2A6E02Wh2ZN38+juMwdepUAoEAWVlZUTXU4yEYChEOh8nIyODE\nE09kUcz9YPDgwaxdu5akpCRzzZcE2+4h7aJZhGZdmj3Z9hptaNaTQxxbbQZm20gikUicnUXey/eS\nZyLVReLZfSq2G2i8NkyzIwm2KqVtP9oGI2Wxjff2Kq0+K8ve2XCkyapVeVuN0nsSbSCR9MVRVTNI\n2xYk32mD+pGEl/bBs+1RR1Jv9TixBU4ipnks4V9yT3Bdt8JxnM3ACcACoqveucSzqlxgVezvIiDJ\ncZymFqvKjb37wXDXXXeRmZkZ9+yqq67iqquu+sHvbEOxNKqewBr5H330UcbX1eHU1zNhwgRqa2sZ\nMmSIodjLly/nzJhKeMkll7B27VogeuVUeno6paWlbN68Oeo0V1dHQUEBS5cupbq6mqysLMPMQqEQ\ny5cvp02bNqSkpLBs2TKTjgDVpk2baN26Nc6uXYwfP54dO3bg8XiYMmUKzVu0oDZ2drjH44mqjrEQ\nCATIyclh3759tG7d2jjwSR3tSWNPFltCSxtp1VG+g3g1Rmwy8rd8Z29Gtm02tv1FT1BbuOhJpyeX\nZkJ6ouln8rcGH10GXSc7H30Ch2YOmvXo57qdtCpnx9OuF0ey/em/E52sqX8089T1tb3VbVan1UCd\nr80EddqaNWr2KyEcDrNq1SpWrlyJ4zjMnj0bgIqKCn5q+JeAynGcDKIg9ZbrujscxykChgNrYu+b\nAqcCr8Q+WQE0xOJ8HIvTDehA1N71g+G55547pvOoZNlc2ytsu4KeMOPGjWPQ3Lm0276dcb/+Ne+9\n9x6RSMScellWVsbsTz+lWbNmfPjhh4ZRid9Qbm4uV155JX/6058AGD9+PD6fj0cffZT//d//jeZ7\n//14vdGTNHNycvB4PIaBDR06lG+++YZIJBI99A7gnXeor68nNTWVJUuW0K5dO3Zt3ow/dphfMBhk\n7dq1ZpC89957XHvttbz++utcffXVTJ06lTuIn4y2vUAPZNsdQNqqPuZsKv/rC0vlO9vDXbOhRKcB\naHeERKpWIjXHBhf5W7Mi+V+Dg07TVillrNhxpc5SBqmH2Id0W0n5NCAIsAhoanVWu1YIK5NtSwIY\neuuPDYLSnrbKmEg1ljayGZf0vTBjnZatZmuA0mxRq5FaxZQxMmDAAPr374/jONweOzBRnUf1o+Go\nVD/HcZ52HGeo4zgdHccZTBRs6oH3YlGeB+53HOdCx3F6AW8De4FPY5WoBP4KPOs4zs8cxzkF+Buw\n2P0/WvGDxt35urPh8I2a4l7w0ksvsXLlSoqKipg0aRLbtm2L081HnXce9957L2effTYlJSWMGTMG\ngMWLF5Oamko4HGbNmjUm3ffff59p06YRCoV4++23jdtCIBCgRYsWOI5DMBg0K3Ny+UJ1dXWcmlVS\nUsKsWbOorq7m9ttvp23btmzZsoX9+/dTWFjIwoULze3CV1xxBTk5OZx11lm8+uqr5ioqW32QOgWD\nwYSD0VYT7AUJW7pqW4ieDPZqkqSrJbUdbMPujxlqId6oL//bLEGri/aigQQN0gJIEkfS0sCjgwYG\nyVOfYAActoFY3tnCQ7eZjmvb8DR7lLgadKW99cJKKBSKE0pST/vMKYmr07cBXYK2Qdos+V8JR8uo\n2gFTgWZAMbAIOM113RIA13X/6DhOGvBnog6fXwOjXNcNqTTuAsLAdKIOn7OBW/+VSvyUYOv4tioi\nUjg/P58LL7yQXvPn02rXLm647jrWr18fxxCaZGQQDAZp3rw5v/zlL2nXrh2AsVlB1JXg+uuvhxde\n4PzzzycpKYkLLrjA7NXjkUdIT0/nvPPOo6SkhHA4TLNmzWDuXLp06cJvf/tbMjMzzYTweDy0aNGC\nq666iqZNm1JZWUlaWhq92rWjODeXVq1aceqpp8ZtywiFQvTt25cBAwZEB++UKWa/n7YlAHHL5xrM\nJWgQk/bSrEAMzHoTs45n+1Jp1VKe6fylTJrl2aClGYa2Sdkqk+SjXSpsliITVk8szXhstU4ASrMf\nDW4QzzRs0NZ9oMsjKqC9gqrrpNNPtClc2kobtjW704JC29kcxzHOoUCcV7uuv70qq9s6UTkSCaGj\nDUcFVK7r/rAxKBrnIaKrgUd6HwRuj/38R4LeWPxDS8Yej4dLL72U2tpa/D6fOSHzxBNPjLtHTqsF\nubm5ZjDJtVcNDQ1xoCF+VrZ6IYMzKysLv99vbGDiFKonpgyu1NRUY2x3gAErVtBn3bq4LUAAv5w0\nCTcBA5HBraXo0QStumigkIEpbh62dNf5S7DVOGm7I12YKd8kCjbz08BqsyO7PNoOpr3n5b1moLZP\nkgYKyU8DQ6J6S7snsvUlul1G4sspD3oHgO5D+39d/kTMRlZD9SZrndaRANVW9SSuLrPka9vEjjUc\nF3v97H1g0KhWhGLe4A9MnJjw24cfeeSwZ5d+8AGXfvDBYc+PlMZ999+f8Lm2QWgDqV49cd3oeeK+\nhoaE6Xz6859HQUrVz+fzEXGjzqxmgDoOJ65axYTf/z5hWRKVLdGEs9/L31qFsC8K1WnYE1azFm1T\n0nYpbUi27R86La0m2dtdBJC0/cWW/H6/39zhqDeY22wS4pmiVgH1Sp1dXw0aYstLtEFag7cGn0gk\nYmxliYSMjqeZj95faKer9zXqNOy6yjvbRwuiaqHsN0ykcgHJYRIAACAASURBVOvnxwpWxwVQaSkn\nDWh0bJ+Pxx591MQV/Vx3rG5c2whvDw49ibRUkWVk+f/3993H7++7L2F573/ggcOefTdwIHNitjAN\nuonKeCSJuiG2EKFZlcT3OY2OgvK9XhXTLELSkN9a/ZPngUDAMEMbkPREkPS1r5Ne2pfJr10VdLDV\nPAl6xVLe25cZaJYgadl70yRuIvZtg1AiJqRtVbrPEqlJ+lv7nYxZW9jaKqkWGrYdzm43UYcljnwv\nba3bS+qr1XBJIzk5Oa78tnCzWd+xhOMCqBIFmQDJlZXc/W+6EebfEeaNGMGyn/0sDuy0+gHx9hI9\nkODwJX8gbkldnustRXpiafuDZjeStm0ATgTcruuawSs/2pNa10v+1yxG1xMaL1rQZU2kxulg182u\npw24uj62+mOru5ol6DQlDQ10GpRttchmehpoXLfR/gWY41TEhqXbT5fLBlm7rex2l7x1fWyhK8+O\nlOaPPbdV/GMJxwVQJRpQEH9kr7AqeX/a7Nl02bmTyddfH7dU+79PPMGXY8awrmfPODZx/wMP8Mpd\ndxGM2Y+SkpJISUnh2scf595x40hNTTVA0NDQwIMPPcRrd99tBl5OTg7V1dX85umnOWvu3MPqcKhl\nS/5y111xh+xrJmFLYmicGPp0St0mIqVl9UfaRN7rttJL13oS6glsqxZSBhuoRIXQLE1/L6xKg6vt\n6W2rjHoD8Y+VXddRTx7JV4zIeqLqeuk8bNuM7flte8BrBi7ltssif+tTNfSChX3ss60KJ2JrUm89\nbvSP3riu05Q8xPVGHErl/C+dlm4f7Yd1JHX9aMJxAVQSbNXFZhV6Uh0qLuYES9+WNL5btQpvzIt8\nxowZnHFG9ACJspwcIpEIH374Ieeddx41lZVcC2zevJm6ujrq6+s588wzzeAszcmhpqaGuXPnEolE\nOOusswB4InaHnQyS/K1buWTKlMMASNfLlpLaRnEk1TDRZNTszWYgAh4ysBOxliNJWRng9nK75K8H\ntc2sdB4y+QUIpD8F+DQjkKDzTWSfsve+aUZpX4Khg6hWeiVVnks5dfltUNZAoJmVfq/bJ5GqKGVI\ntK1H94/0n45jjx3NpGT/ngTpF0kvEAjElV9/Y49Pm30eSziugEoHu+F0x4nTnZxMoN8DZGZmUlRd\nzUcffUR1dTVff/01AJWVlXz//fcEAgEWLFhAz549Tfzk5GTy8vLweDwUFBQAUb+rQCDAvn37OPHE\nE3nnnXd4mvitHY7jEFZuFPak0QzEtgHZtoxElNxWFeyVUWJtoM8yt9/rv49k5BVjte1GIHnqbSlS\nLr0IYk86+dtegtcTTpdNq2z2iqTNzHTaidQ83Xbyve4vzbSk/jb7EfDWHuY2+9RsTeeh09dltF0m\ndBuLV71W5Ww/K2FN0s/6aCBtS9QXXeirtI4ERtKHmvkfbTgursvSA1tsA/I8ka1C2EIkEqG6upr3\n3nuPQCBAVVUVwWCQwsJCJk+eTLNmzejevTtnnnkmANnZ2XTo0IFgMMgll1zC999/b/IpLCwkOTmZ\nhoYGw5yGDx/OBRdcQGpqKsOGDePOO+808WWiissCNDpoagovu9tltU07Ioptx3VdQqEQodi+QP29\nna5tlxHGoNmAXQZbytfX1ydkUHpSyXutWkh55Z12SI1EIgSDwbh0BTR1+eXvhoYGc26WtFMigJX6\na4dMmYzybaJ2l2Ns9JiSNpJySp1CodBhfaPVMV1nyU97l+tvIpGIuUnHBmqI36+o+1cYl66LlM/u\nQ1tllDaWd/pgQVH/dB10eSVoED6WcFwAlW2IhXhbg/yv33tiKywAl1xyCSkpKTRt2pTk5GTatWvH\nr3/9a9avX8/u3bsNo5IBVlJSwhtvvGG+9/v9pKammo784osvAHjzzTeZNm2aGRACSnrQ2gefQbzX\nNGAASAOUjqe/1zYUfWyHLbV10CqVpGEHrXJ4vd6EToGaEdhHhmj1VN5rMHYcJ86/CuJPfJD/7TJp\npuK6bpwvnA2G8o1MOj0mbIZkLyLod141duzy6bJIe0m+GlzsNO3/tY1LpyGCRZfPth/ZQTNSbXfS\n7SRBb3q27aGatdqLLjresYTjAqj0wE9ElaERzMwxHbHBJlTYdV1zUUFNbS2rV6/mlFNOwefzmU3G\ndXV1bNmyhQ4dOjB69GhycnKA6Cbmjh07UlJSgt/vZ9iwYQB069aNESNG0KZNGwNyEL/1wTbGaimq\nJ7Cul/btsQ3VED/p9MDRjEoPVntLhQ0YGji0e4Htla2lubafadVCgMIGLg0stgqnVUR7ImhwkG0g\nmjFKHP2/fi7/S/ryvwCEXta3g62S6jTt/CW+dhmxDfeJ7IzSPtqOpZ9JebXQsu2yGlhsu6P8FqYm\n/aadYqHxKCVbaNhCIBG4/5RwXACVnjRayuoBpreQOI5DJNaJsswucYPBIGmpqbRo0YK8vDz69Olj\nTk+QEwo6d+7MoUOH2LRpEwB79uzhwIEDrFixIk4F2b9/P4sWLSIvL4+//OUvxoNdymwGS4JniYy8\n2sclkcTXg9420Np2GD3B9bdaxZLn0q5ir7D9xjRTEMYBiR1xpQz6mBsdT9tK7P611RfbZpcIBDSI\naLDRrEgbyuV7fXCe1EvKKfYaW21KZL+Tb/UY1WXRfSB5S7m0uqn72ufzmRNKdb9pu6WkpcFHp22P\nGdvuqctqszp5Z28HOla1D44ToNK0VNta7MlcXV1NZWUl5eXl0c2Z9fXs2bOHvXv3Mn36dFJSUkhK\nSqJ79+7MmzeP5s2bs2DBAk444QQgeqpCz549CYfDZGVlGVvU+PHj2bp1Kx07diQSifDMM88A0TOj\nhg0bRufOnTnttNN49dVXTVn0hNNBOl5vLpXn8k0itpIoJJqgOg/5296IrKW1/Z195ZZt7LZ/NFAm\n6hc9YROBk/wt9dTlFoOw9jCXSWPbKW11VpfHXlpPVEabpUnwer2kpKTEuXAkYiLavcJmiIlsVrY9\nSQexsdl2QF1uGzxsd5BEQeeXCNC07StRnP8yqh8JdmdpD1/NtETap6en06RJExyPh5ycHFq1asWF\nF15oBsjBgwfp1KkT27Zt48YbbzSAJB2fk5PDpk2b2Lo1evlOeXk5N9xwg9m0K8dcpKenG5WzZ8+e\n5lwtbTDWA1/biGyJnQik5PhZfayKbSiW5xrA5X8tGSVodqQBRoJWJ/Rk0tJV2+60KqLVBT2hbZXV\ntp/YxnD9rWaGGgQ069K/df3tvxOpbVrVslVgDWbS93qfp1bRBSg0iOj+kPpL/QS8tJqsQUSr0Rpo\ntTqo+0dfs2Xb17TAk7LJmBOXBP29lFczsEQgfjThuHNPkMYUg6OEn331FR7VsB337KHT3r08+dRT\nh6Vxx5Il3JEg7eeefz5hnk8dwfP9oYcfTvj8wYceOuxZvTWRNGBoB1DbHiL/20vo9qTUEwTipZ+e\nBDK5bDuYHtz2RQaJmFuiMmj1TQOEZgGi8kr62p4ngChqj+yLE6DV9kbNQvRVZbKgod8nWi20AdFx\nnLhbhSH+uGO7rjoN4LB2lXi2z5jeg6jZo15AsQWYXR+7fSVIGonYrATtTqHroRmjTkPUQg2MxxKO\nC6CypY02BNamp7OjUyc67NkTjUtsUHm9PBIDEs0Y4uxY1uTWqoteNtdSW/uc6LT14JHJqM/R8nq9\n+JRU1J0v0lg2mAJxk0Ikq9frjTv0zmYF0j5aCmoAsu02kkeiq9T1wJV8bPVJx9cTWBilPudc23g0\n89A2Imi0E2pGoy+m0CBn96kwC90+un+lTnp3gF0fzaxs04LdJ4nGp23AT1RfPZZ1m+m2sm1RGjB1\nGbR5wRZ2ur/ssa6f2yxajykRZImE1dGE4waoJNiDFODta6+N+99IBtWotsQA4tQFW+eXuDJJpNNt\n25KUT3e0ZhDivKelpJ7YdtpwuKFdl9MGKQliW5J9gTJpjrSCdyTbl14Js1Uk7YQooKDbSrel7itR\nMWxbiw0g9rc6b2lTPdE1oNgsR+eViCUk+i4R89JsR5fdbn9pLz2h9amg2s5mp2eX0d6RoNmVrp8N\nPvq567qHqea6PWzhZtdLl0m3y7Ea1I8LoEoUEkkcu9P1+0SuA5DYO1sGhO2X9GOT3FZHhFloT2V7\n/5hMQNvPR+cjg00GoB70Ek8zHD3hNSgkss3osmvpqleBdNsKkNnS2i67DnpySflsR0etiup20X0m\n5bTVSS317baw6yl10iquXQe7P+3JrhmUzYCkbNpJU/e5PW7t/tAAJPXSHvA6aDVS0hFtQ7NQLXxt\nkE80Duw622z2WMJxYUyXRtUS1QYkbajVzog2IOlBrTtLOtiWdlq1sw2uiTpT3mkDuZ58eoLqH1ua\n2wApPzZ4aiDSIGbbFXTZbEDW7Wr7WOk21IbZI6kAuj30qpUuWyJVxW7zRCqI/Jb+sg3NidrTZhOJ\ngDBRPF0+m0VoZ9ZE9Zb0pR808MgCia6TFloaoOSd3tBt2xJtu6So93afS1o2M5f39o/EOVIbHW04\nbhiVXlWxJ7OwFulI6Sz5X/9OdKaRBqGkpCSzxcGOJ3uk7Mmhl/Mhfi+X7Leqra3F7/ebG4TtQSSA\nI2dx2wM/kYogeUkcv99PIBCIWzJPJMGPxDwlXfudBkJdFnknaetgqxg6/SOpytDIrPRJo9L/YjTX\nKo9mUbpNbCEhaQvI6CNY7PLb9dfArlVgfaBdIvan2yu5poackpLDVCtX5xn7PixpKTYtbX7Nyy8f\n1mcAb99yCxFJO9Joa732tdcSxj9SePqPfzR/y9jS8+a/qt+PBE2ftWe0HjxiwNaOi1oSa/qsJZIM\nfL1pV0tTPals+5E+KcC2zch7x3FISUnBcZy4q9IlrgTNaOR/HRIxEA2mkrZmI1qN1WWUb2010fab\nknQkJJL4tgSX51pV1UxMCxOIPxFVyqVVHslLL04kAs5EwKufSTp3PPww3gTbiI42JIVCPx7p/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GtbW11NTUmLSvvvpqM3kAo7JpZ04tJbXHelpamqlvUlIS8+fP55tvvmHv3r0MjZ0Pv2XLlii7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\nphGaSVheXs6uXbs48cQTmTlzJtv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kM4aSDoJKMnX4GvlMoc+hgbH8lTgrx/dd+VqNcy7y\nYagpZtJKJZmVq/mqNuXXz/e3+HWyiW5aiKrqqr4bqeagAG9MrL9pe32zz/e7qLPY/vc1Yh8U1VTT\nNL6JrqCliwXaVyo8NPhTtTI13+1ddUhrH1n5JgSa8mNa3xgIq4ZiaRWkrW6mVdnvlsZi9nwwU7L+\ntrTWPuVfA2Td8uWcI51OF/CAfm+K198PUL2fVb9rgMeDINj4PvJoFl1//fXRSYxGU6dOZerUqfud\nhz9YRjohofBiRR0wXyOx/31V2EDGV5mN7F1T53WLgko9X2r7jlDNT7Uha48eWWwTQU2ZOIkXZw6o\nZqSSMs5ki3vXlr3VCe1rYH49DACtntaWuFgmKAyyVdIJpaAQV097ZuOvmoNvImv+Wgero65S+kBh\nwKeA7cf7+VpcHAiqpWD11vAH35Wh3zVf5Q8Fd6urzQWfN2x81EdqpGkWLlzIokWLcM6xYMECIDzh\ndn+pRUDlnOsLnE7oezLaCDhCrUm1qp7APElT6pzr4GlVPfO/vSf96le/atFNyXo8hsb9qITwtSAD\nBd/HoSaIPbOBteVxf6kdGvxYqjb7zGt1M8YwJtKJrvVSBjPAU+3R3lOntW86xQG33QqsW1tMalq5\n2jZLr9qHTSTffNQJZwCkdVezycwym/jmkPYDdW1MTDPwfWDqh7L87a+GNuhktzytXN9nGDfhffPL\nfvcdyVZHG2+rox82oeOvY2r18p3qylPWNiBacTYTV8Mi1FRUnlDBqIst6gfTdiuYWR5ax+HDhzN0\n6FCSySQ//elPgYKbkvdJLTX9riEEo8fsQRAEKwnB5jR75kLn+Tjgpfyj14CMl2Yw0Bd4uYV12Sep\nyWQdp0GMKoFsIHxTUSccFJoIlt4miJ2eoBqGApeq0/ae2f7GrL6Zp9JK/RRWdjqdjiaqMVqcdqGa\njLXPN8nsu9XPJqvFy/iam04sO5nSB0DVkBTsFdhsdU/B39codWLquPjaoPpkVANV083S2wqr5eeb\nKbpKa2Nq/1t/GBj471v+aprqJNatP76vzxecmr/vszRhpfzqh7zU1dVFISw6hmr+al+qgFYzW7VM\n61P/tM9kMhn51VQTbCk1W6NyYamfBm4PgsAXx/8J/B/n3DJgFfADYC3wEITOdefcn4FbnHPbgd3A\nr4EXgw9pxS9fZ4CCCawqqoIUxGtLOoEtP53YGplteTYlEX0JrLfrqqljdVAtTFV+9bNo2X4dLB+f\nYbR+6pcyLVIB3dKrOez7mNTEsbJ9KW11UOHga0c6Ia09anL4Zqjd/Ktgo1qVrkrqZLN626kYWgdf\nI7IJr8e4aDCpaq+av5pGyguaVk1dFS4KVlaOkoKp+lR9P6W6Mawtlp+BS9y+PF391AUXA1nLW/eO\nav2t3R8EWLXE9Dsd6AP81f8hCIKfOefaALcBnYBZwFlBENRJsuuBLHA/kAaeAL7UgnrsN+lEsMH0\n1XfVpHxJZhNQO9wG16SGPfPBzLfd7TdjZC3PBxj1NfnmpzGEgqouC2tePqNbW6w/tH80gFAB1fe/\nmSakmqmGZehkjQtw1DqpeetraJaXTQ4rQzVa61/VWnwHvE4U60/VZLQv9IQGLUP5Q/tJx8V36qtW\nnEqFB/xpnJMCjIWqlJaWRsCoZqPmpQCm46ntjOMf62PLw48x0/xtfFXIqODOZrORKa68YWSCSudT\nS6nZQBUEwdNAk1uggyD4D+A/3uP3WuAr+c8BIe1olZz6u0ptX0L6aZXx7Y46ZVIFEx/0lPznqjXE\npTcm1vor82q+aoL4DKRgqhqbka89xjlQjcnN76HahZajgBInIKw8X4tV35qCrfrkTBPyFxj8vldB\noIDsT3wrz7Q9v599rVh5xkhNfV+INOXst3pb2qZi6LRsI9VYlG/98dLxNiFj9dED7Xx+VFDS89F0\nfHVM4wSDr622hFrFvX460DpgRv5A+5NUmcSY2BhE44EUpHRimiYQVxd/ovirPfabTizzqSgA619f\n2r7XKqJv2imj+lqIMq4ypvp+FCDVpPDbChSYkL6m6vu5rB2+QFHzW31c1j++cNKx1Lqp2RRnAvrA\nZdqhmrlq7tq7OpGbMsvsu2qL1q9ahqXTfPXgQR1fbZc/TpavauGav/olfbBX578KcV8gqzmrdWsp\ntQqg8k08Aw77NMVEOtA6Me27aTi+uefnYWUb6eT0Jab9rqDkO2CtTn6Etr2rGoQPjFB4sqX+1TbE\naXS2kqTlqo/FL8/XAuLAQs0T6181KXUc1OxQwNLtRjaWSv4kUp+akgKn/9z3G1qdtF3++/4KGBBp\nVuY20PG3/vOBX7VG6y/fmW5t9k9WUN+YbkXyXSC+xunXW3lG+VMFpi5yaB/75nFLqFUAVRz5qnAc\ng/tkEkXVX7sc036PmwD+7zppoLG0VqbVpX7fRFVtQieXOkjtfZ1c+yLfFLT+ggbTRv1gcW2KA0+t\nh2qrpvEZmaajy+8KXP4uAH+lUPPWSaQrYAocqsWotmZ52rirNqrbaHytWYWa+iHV52PakAKOlWkr\nktbHKgysbuprsmc6VurAN/D3xzjOXFPN2eqvdVPfn/GBaXgaIOtr574J31xqFce86ATxwSEICqN7\nlRlUffclnQ6QplcJa4zix6ropNaVO3OomlmhQASFRxBbPYwJNaLb1860PAVSZcr3mgy+aaYrfbYK\npuanai5+3/ranPatb1qa/8/8IyqhFXR1Y6+BjuUfB/A2/laO1s/e1eBUraelsfzMT6ZbnnyNWT86\nTqqxaD/7WrbWUcnnN3UF2Mc3b20FUM//t37WesW12/KBcEXQwnBUa9Mz0nyT2BfIzaFWAVQ6AX1H\nsUpmX9tQILHvceadkb1vE0nPAVem1/eMkZSBVXuI09C0Lb4k9NP6jOy/Y1LSZ3ot248Zs7ZZmXq8\nrWo2ugVGQSbOx+UDgJpaGuiazRae3a7grRqPgrFqJgrOfnt9UFNeUUFlZ1olEolowuq4aL/7PrX3\nMvmNFCh800n7zAcvn1/j/J3KY3HjrZqmCgMDbjP39FhtX3DGtU3TtYRaBVApg+hAxqmiqnUpeBmz\nqBPRHwgrw18dUlPOz0PNSC1f31Vtxq+rlq3+CW2jtVvLUUbyfXOq1vuSUE0RNV8UfPxJ6oOR9p2/\nSudrHVY/389hH10h1OfaR75/x8w8HZe4sVIt09pm2p31i53XrsCh46QLAD4f+BNa26TPfI1WtXN/\nLDWtxmoZmYmmfGB/td0+jyvv6Ps2Xr6v0RcW9mmpQ71VAJXv//AlgR7P4qvperGlbbXwY1H8SeqX\nrXmqc94km5Eyhx5GZs+gUNL50ksnhV8nAwNlZGuzTjBf+vrArAsQcSCsUlMBwwcRH2QVLHRhw9cw\n7XctR/vA1/5sUvvpFJR1cmn/2wqXatwKvspP2k+6+qtplB+0T7RemtbKVKCOAyVdaLG4JuUpBVsD\nC19QKJCo4FP+Nm0qLljXX3SKmw/748c5ohMAACAASURBVB9tiloFUCn5EtSeQeNJqYxpfiB10sb5\nvuLK8/O2/H1Q8DUTKAQ0P6LeJ5VY6jT2AULNUR8YLB/tA/93yz+u7f6k8CejtsmEhGo8Oj5+nn7f\nmL8lLjbJ2mmTOG6MfJNfV9ksDy1f443ea9LFAaEvBBRA/DGK858poGtefp9YWgta9Z3Y2l6/zla2\n8pxqZ3FaktbJ1wQVGH1B3VxqFat+pg1Zp6k0NKZQkLDON+lhvze1rK0M7jOkanNxarwv5fy4GdU2\ndKe8TmpocCgr+UCsZVq9NdxBpayfj7VJ66t188v0/RWWr8/gQVB4GYEt32vIgdVTl9Zt/HRcrA36\n3X73TTi/DtrnVk8tV/vbN3207nFapD/+2ndaPyXtOx8MrFwTpAb4NpZ+P8WZjn77ta/1PV/I+GBv\nPOGb575WqOPREmoVQGUdFyeRgqDhuuxcrjBo0wY9Ll7JmM2YzJjB39xqK3gq4eO0DssLKAAr51wj\nE8TKt7J1UisDmqquElInRdwEM6a1fvNNDt880Elgp1ToWeW+RFftxeqifjpfImu7tB5WP+0HPz//\nHb8NVj+/XBVIvmAACo4y9sMc/PK1/X6clW86aTus7+NMRfsoTxvZbz5g7cs3pJqz5aG+ONWKdDVY\n+d4XUspD/pg0l1oFUNlFkOo01sHXIEagADAU5DSmxJfmKo10wuzdu5cgaNhd709cKPSTKBMYSOog\n+9qGmjW+pLZ9XFZXbYNqcErOuYLlfl8LUDPMJoC1TSW8Dwq6GAEUtEknppLfT/q+hnMoeKkPKa7+\nCjr20XpY21RYJZPJAt5RcLM6q//PBy3VelS7SCQSkTtBT2iw9qnm6IOR/fX7R/O2/PSkiKYAS2++\n0b5T0LY+9wWyBa4qyPruCwWyllCrACrVKFRz0tMUNR3Eq7hQKAWbmkhq9sX5ZjStv2Llazharkle\nmzgGNL6fQuvl+1tUgqujVie1apAaMKqAYxcVaJ4QCgXTCC1f3SPmlwOFkzxOW7I8fBPG/qpzV4WE\nD9was6WajUZf+05hBWJfs9MxVn+O1SNOA9fy/DpY3XS8zaHtA62/iuuvVFoa6x/VENW3ZW2yI3ws\nT9XC1MqIA0cdG99a0TruS6t7L2oVznR/oKDBbwUN99X5q3l+xypDNqVuqwZm7/hM7W9OVebTSe+T\n5WuMpsCmvgVrm9VHzSo1vWxC66FxVhfVKHRyJhINsUMa0Gr94sdXxYG55WWnBahZpAIgri/igELB\nz9pvE1Qluf3f1MZgvwxdSAEKnOlWti8IdJy1TtZPekyOzxdqXpqmYu8q+NkY+BqX5qHjqz5W5U8F\nfn97ltZLeUj3Qmo6zUP7UMmfN82hVqFRqZT2J4I9j1vZst8UsFTi+gykEk8nvNbD3vPrYr/r5NQJ\nqGlMG1ETRMu0tqj5pwzka1x+nhpnpGaTrznESU/zU/nttnSqvdh31ahUclsZUBjHZu1Wia/jbGl0\nMUQBXfNQLcHvQzN1bK+faq4KrP6qom+Kax19TVH7SIWCnkKrQknf0XFVAWag6IOov2dRyX7z54D2\nj79g42tpWp7OGf/SkJZQqwEq38aGxpuP1fEMNFKvocE3YvlqPva/Daza9xbe4E9WaHxtu5EOqoJL\nnPSOYxQf8MznpXW18vWvgqWlt4lvmpqChb8iqpPB38CsbbG+0HsNdcKphqhmctxtORbfpmWYD8j6\nxzej/L7yzSH1Lxk/2P+2/B/nuFcntk1+e8+/TMHMb9uOYp+ysjKCIGh08YLWRZ8piNgzPfE1LvzE\n156MDIR1n6m6CHyt1Ndytd/UBPUFd3OoVZh+/vKv32lxS7LKrPYcCk/RtHxLS0sLjr+IG0yf1DzQ\nv9B4D5c9U/PSmML3jahZ4UvOOBNPfV+Wh183NRv0XHP7zZha26DagAKEalf2v66G6dVVQGRWap/7\n4QFWZw3GVVBXMPed7zqZ/PrpR00p31Q1IRg35nFAoWT1UODTsVFzz39vf8won6/iBJ6vqakPTFdk\nfbL3fFNW2+DHchWB6j0ozuTzJ6ulM3NBzRD7zf+rWz1U4tgzf4VHf/MnovpTfKbUyaEDbhNPgUon\npYKdn4f/m19H+x6n6RkpkPuT25hcJb1qVnHM7DvMtW8VqK2fzE/m10M1YQMANQs1b9XMFLT9iQeF\n4Gt1VD+Q9pum88MSDNjVZeCDVJxG7I+BttvvM62v1knHWeeApTVetHr7bg+ti80Vf1uagqtZFv5i\nQXOpVZh+Ojl9P5JOWH8S2bM4VVnJ9wX4ks4Gy3/m+4R8J7Ayl+8TiZPcymT+SqDmq/moZhjnL2tK\ncusKnj+R/JgaNel8zUq1KvOnGbNr/9o7Ogl8waCTw9cMrS46pj4w+3xhdbO9fH6/xMWoWX5+iIfx\nj/a31cUXopZW+0ABzHd6W59Dgz8oCMKVPA290DK0T7Us4yvfAtF3tC1x4Knv+JpaS6lVAJUiuj/5\nmtIUjFTD8ZlJB90GXCeGL7XiBk6lf5xTVqWS5mfptc56vKxvbvhA1lSeOuF957J+fK3NJptN6jip\nrhNZ/ULm/9IJ09QEUO3EB0jVRAz4FeA0LMA0M/+cJn/cLG19fX2jc6Ks3gqIOsa1tbVRnawP9bvf\nfxqbZOEzPs9a29V3aG20eCb1JarZqjyr/GzlK/D46VRLVODzhY71g4aoWF/b85ZQqzD9bAKpU9MH\nHPVlKPI35dvS/BQENS7KBtbAyGcWNfcUSNQchcJD3iwvX0tUk0jDLnxtMU478pnMnql2or/5/aP9\nosAUJ0FVQ4w7cyvOhNHJpLFwfv7qwPUXR/xQBUvvB9Tq+Nt7eoGBjYMJAgUza59qrCrErH16YJ4G\ngfpaosU2NaUl2pn1aiaqgHovDdTar/2o2rYvBFQz8/tG66a30Vjb/UWqllCrACoj7Xj7rkwEhQfa\n61/raJssyow+QxhI+SqzrwGppLE6KAD6AZLQ4Dz3g/Di2qhg6WuBcRqA3y8+aPv5+uDi96++p5eM\nWhiDvaPkm2t+X/lgq/3gm65Wtq9paZ39vrQxNLC3MTBtxe8LX5vSu/V8UytOIOpJnP4pHto+K1N5\nIZlMUlNT08gM1FVcFTTal8pPqtWrdqUmr2rNJlz0th7LX6/lMpAyP6qNeUuo1QCVz8CK+D23bQPy\nTK2mTzYLzuFoYLpUKsWPH3ywWWV/9pprCqSvOi79ieSDg9ZZJ4pqXcp8yniq/iv4qCPXNBSVuNpH\nChBxfeo7T+1/Y2JzeEM4KSxYVLWCuPfVj+QHSdpYqBmroScKOJqfmrK+9qc+Mktr2ooP3Kad2c3R\nvnarQkYXMXQPpaZzzlFdXR3VyfKzA/p8czeRCC+c3blzJyUlJZH5qiumvv/I+lGFs4FTbW1tNA4m\nRHK5XLT7oKamhvr6+sjnVVtbGwWcWp56tr9dcqoarPFPaWkpv/3tb5s1f6AVAZWSqtwdamv56cMP\nN+v9v4wdy9yKCl6dO5d0Os3xxx/PLffey6evvrqRxPzvO+8sWLpWHwU0HMSmkhMKJb4dHQuF5x+p\nBmNRzMaANlF8ie+cixjJyjfz1New1IxVaairc/4igW9a19TUFEhiAzFfYzVSv5EfwW/5qu8JiOqm\npp8GQlr7IASkqqoqOnXq1OidNm3aFGjUGhahvqi9e/eSSqWifZxVVVWRRqQmXX19fbT9xswkMxst\ndqy6urpRP1s+eqKBgrSas0AU4V9WVhYJF42BymbDU1EtViuZDA/PS6fTEehpfFcqlaKkpIT27dsX\nxKFZv1sZ1p9WJ6uHgryarVrn5lKrAypfwtrEuvpTnyr4/fw33qDX4sV847jj6Nu3L845Vq9ezSOz\nZ1NVWspTb7/Nx049lc2bNzOvshIoNNt0sii4AI0mp01cVb/V52GSy971/SnqELa84vwt6uuxcnwQ\n800r1SLsu/6vqz8KXsbgZj74x7ZYX9ukNgZXZ2tNTU30LJPJRGBsfasriuoDtD7XyW7tMwCxiWV9\noIfEWfvS6XSk4VgaCLWC8vLyKL0BBDREeBsAtG/fviD8QkMlfBDweVJ5SSe48YC6JbQNuVyOq599\nllw2i0skIJkkyOUgvzm/gIKAABi/dGnjydICmn3UUeAcqBXgHHecdlqsm2F/qdUAlQ2u+n9KSkrI\neLfIQKGdvnfv3mjide/ePfp96NCh5HI51q1bR79+/QAKAj/jlr5tkvpXGvnqsflErK6mlkODD80H\nOt1SY6tNuppo0txfedq7d2+BGVZbWwtQsJvfLsTU/WXWDzbxVMoaeNmkV0BLp9MFE9x+s/ftWTKZ\npLy8vOB3e9dOXDVAsL9KqgFo3zrn2LNnD+l0upEpre1QMDWQUIBQzdH++gCi5fq/nfPqq3zitddi\neXXG4MGsraiINOlMfT2Hr1nDmatWxaZvil4aNIiEmbf5Nnxs8WJmDxkSujTyPNhp927qk0m++aUv\nUVNTE2mW/zJ9Ous7d+Z/JkwoiBO87Q9/4PtXXcWmtm2jsvbu3cvtd9xB1gA37zZJpVKMX7iQP598\nckF/NJeaBVTOuQRwE3AlcBiwHrg9CIIfeuluBq4lvNb9ReALQRAsk9/TwC3AZYTXuj8JfDEIgk0t\nasV+kK48qG/F7ziVaIlEIjqrChoiu7PZLG3btqW6uppEIkG3bt2AECA2bdrEnDlzIi3gHmD69OmN\nfAYmqe25P8lViltaU9X11plEIhFpBjahTMKbj8je8cMVrHx1fqrfR6W/griaiAb6lrc6yTUPa58B\npZarDm5fs/R9a/rdxstuVPEd/2quqsmUTqej5z7w+M+s3nrSgzq0TVs001yB2+rhm/rOOQJg6WGH\n8Ytzz6WyspLevXszY8YMXl66lDErVjBk+fIwjyAA5+hZW8snr7yS9u3bs2bNGrZt20YqleKfs2bx\n5S99KTK37Pq2P/zxj9x56qlAg5bdpk0bPrZ4MXeeeiq1tbVUV1fTuXNnjlq8mC9v3Bhtut62bVuB\ngDFtVseqpKQkWvErKSmJ2n/HySdH75jpPn7hQnK5XMS/LaHmalT/DnwO+BTwDnAccLtzbkcQBP+V\nH5h/A76cT7MK+CHwpHNuaBAEdfl8/hM4C7gI2AXcCvwPcGKLWrGfpI5WMwOs49Xno85kc3KaNpDP\niCAI2LhxI8ceeyyvvvoqEA5eRUUF559/foOz+847ufjii2PNMSiM2YlzuCuA6LG7Vkf1G/j19xcO\nfLXf8taJp6uQ9lz9S9aPukKlvhNlZl87UY3F8vKBQkFL26wmo5lRVp5pi2oC61K75a2rhnHmrz7z\nQ0B8IFPzPp1OF/iR4rRpBT2AhJRbWlrK3LlzGThwIG7ZMh44/XTuyWTo3Lkzhx9+OFVVVfzxT39i\n0aJFjB49mq5duzJ//nxGjBgRjSPA7t27C1wBiUSCnTt3kkql2L17d0Hs1aOPPsqUKVPYtGkTh1dV\nEQQBs2fPpkuXLnTo0IG9e/eyZetWlmzZwt+WLiWbzTJs2DDatGkTlVVZXU06naa8vJxly0I95OWX\nX+bkk0+O5pYB59q1axkwYMABM/0mAA8FQfBE/vu7zrkrgOMlzdeAHwRB8AiAc+5TQCVwPvB351wH\n4Brg8iAIZubTfAZY6Jw7PgiCOS1qyXuQv6rmq+cAd951V6P3NiUS3Lh3L4e/9BKlpaVs37aNtsCp\ny5fTc8ECqqqqCObO5cz27QG4+qWXIps8CAIUFtR/o5pKnAnhx3vZ3zg/hu8ziptw+kwnr++3UiBV\n8GqqLkb6u24Jsjzi6qdah/oufG1JJ739pqBsoBEXf+YDcyP/jNRJ/7d+jptU/jjpap7moUJH3/Xb\nlEqlKC8v59hjj41M8927dlFx1FFUV1ezdetW2rVrB8CECRPIZDIsW7aM/v37s2TJEqDB1C8tLY3A\nHaCqqoqamho6d+4cmXMQmmklJSWRVtSpc+cCPlLNLJvN0n/gQLZv3042m6Vnz55hmtJSkrW1dOzY\nMdpADaFfsa6ujnQ6HZUB8Wd0NYeaC1QvAdc55wYGQbDUOTcSOAG4HsA515/QJHzWXgiCYJdz7hVC\nkPs7oRaW8tIsds69m0/zgQOVmip+/NHusjKu+uQnC9La36+++CLDTXPJZGjfoQPz2rXDAUek09Ch\nQ+isBF7p2JG29fU4IKBB5Z9zxBEFjnEFGpsUOpltoqvfRSVyUxLJn+xGWrbvlNV3lYG0XPvu563P\nFEBt1S5OK/HLU0Hh/+aDo/9Ml+oVAJpqg1JTgKV5+xNLtU8VNGYuxbkRoPHBehHvhYUBDXc62mpb\nOp2OJn95eTlr164FYMGCBVGQp3Mu9I0uXRrFYpWXl/POO+/Qo0cPAHbs2EF9fT3pdJqtW7dSUVER\n1Wvy5MnRqqTVe9iwYezevZtt27bRqVMnOnTowODu3Rl45JFkMhmqqqqoqqoK+yPfpurqalavXs2Q\nIUNgzhwGDhzItm3b6Nq1K6tXr6ZPnz4AdOrUqRFwN4eaC1Q/BToAi5xzWcItON8NguBv+d8PI5yn\nld57lfnfAHoCdUEQ7HqPNB8o2XKsgYIxnV1kqQxmWkEmk+H3kyYBhRHWmoeSP8EUjIyRNYrY91f5\n9YVCZ3Vcvqq1xIU4WB5WB52M1g7fzLR3/DbFtdvXUFUqWxm6PG3PtT0aoa5L3z4oaH623G518AFP\nAczXkjS9D/763H7TsVLgtZMaVINUTdb6yjQKnaDRSmz+uZ/GNLW2eWe1TfbBgwc3FlbPPEN53lfK\nrl2M7N07yv/Bhx4ijm6/447Y5/99552NH27YwOS33mr0+OYYCwTgsccfj33eqVOnWPfD/lJzgeoy\n4ArgckIf1Sjg/znn1gdBENPKQ4N+8YtfHOwqFKlIhfT978Mvf8nvXn658Hkmw2eXLOGzmxqvK/3u\n97+PzeoXt9/e+OGgQXDvvftfn1Gj9j9tU7RuHWzeHPvTb99n/s0Fqp8BPwmC4L789wXOuSOAbwN3\nAhsBR6g1qVbVE5iX/38jUOqc6+BpVT3zvzVJ119/PR07dix4NnXqVKZOndrMZhSpSAeZbroJPF7e\nJ33jGx9OXT4o6tUr/MTQtGnTmDZtWsGznTt37n/e6r/Z1wfYAvyL9+zbwCL5vh64Xr53APYCl8j3\nWuACSTMYyAHHN1HusUDw2muvBUUqUpH+d9Brr70WEFrAxwb7wJ7malT/AP6Pc24tsCAPINcDf5I0\n/5lPs4wwPOEHwFrgoTww7nLO/Rm4xTm3HdgN/Bp4MfgQVvyKVKQiffSpuUD1ZULguRXoQag9/S7/\nDIAgCH7mnGsD3EYY8DkLOCtoiKGCENyywP2EAZ9PAF9qYRuKVKRDgz72sfjn//3fcNRR7z+fl15q\nfp3+l1CzgCoIgirgG/nPe6X7D+A/3uP3WuAr+U+RlG68sXnpf/jDfacp0oGjm28GIKjdg0u3g6oq\nGDiweXlceinkgzkj+t73yLz0R5IjL8K17fIBVfYjRPuyDQ+FD63JRwVBcPLJhZ+jjw4C54LsSScF\n9RMnRp9cly5B8I1vxOexYkX8c49+9rOfxT5vKn2waVP88+99LwgmTmz8vEuXIPjb3/Yv7w/q+SOP\nBEE63fj5mWe+7/5q9vN8f2V3bAqCIAhyQRBkV78Z5L52XZAbOyrIrn41yG1fG+QyQRAEdVF/5Xau\nCnJBEOTqdxXkna1cEl/2R5A+TB9VkQ4EPf984fdHHyW46CL2/OMf1NbWkk6neeONN/jYD3/Y5AB+\n95bn+dFv+gPw8u693PHNr/N74POf/zwX9kpxxo3/1eid+jeXk+zfj8xtEwAoBep37CB4uwZmnw04\nqMqEz+feTWrgUbh1s6l7az6lVJBb9waZn48FIHnx8ySOKA+j84OAzMy/kNs+kpLzRgPhGV91P/8C\nMBdwlF76Her+ZyWlQGZZFamj6gk9B1A/91VKgCDIkV0DqT7rqfvFBVEdgyCMG6q/9XLYuxK3aCcp\noP6eaSTHnYfrWYYrzxKsXEniCNnn9/rDJEafHdblnmco/e51YT53nEbJ1VE8ckR1Tz1K6rjJ0fnd\n2S2Q7LYd6Eyw8XXiIoSCIFwGz8y+nZIz/hWAzP/cRHLBbNyWXWTu/TzJb84h+8gfYNEfKKnZGaZ/\n5AZSU6dB1RKCDqNj825NVASqjxjt2bOHhQsXMnLkyCiyWemRV9dwNvCjb5wSPXvlz7cxZOhQAIYM\nGcIi4AzqgZLCl7e+Bd12UfqtueH3G/JBmSd2Ibchv0tqVw3wBiXDx5N55h6S595Isvp2WLQSkn1J\nXfJrMi/8jtzG/0fQ/nxS2Rqys/9CbmhbyDxH/R3tSU29EQe4fg7qh0NJO+rfWULJFz8D//qvJKqf\nJvPPnqROCgGT2uUAZB78CwwaQvbtZZR84UVI7IYbuhHulYfUud8lc++3SJ4wFe76NtSuJti7ktxj\nt+I6HkUiWUZ26QosvDbYvolg9dwQBLJrwjLWbqHk6ofI/PPNaHJk/v4xUpe+BG07Q5sw0LT+718k\nqIdcMgNVa3G9joidTMHmPTggNfgkMnOfItm3C4kLbiCx6o+w81VSx00iO/ctUqd8kqD/EPjRWWRe\n2YCbegyZ+74CmV24Nu0b8m6liNUqLnf430QbN26kd+/e0XEsPuXqGz8/57ov0rciPKKmW6++fPXr\nk2gEUkCweR2JXkMKn835EwGQ6Hc0rjRJsKYh/6DfZdT/cxHJYy9teLZxEWT2QD2EUSlA+ZG4TueQ\nGHE8lPSHTeHGVnfCL3G9jyOobUNq8r+Qe+oWALILpxOs/z1BZajVJCdeBkCioozEnmW47oMa1b3+\njk+Re/dNEkOOIdi8BIIcJWefSW7nTlzPocBKyG7HtW/YRpIY0J/s2ncAKL3qXHJA8PjXyMz8K7lF\nd+dTbYeyCurn7CDRphOZp/Knu/Y6nkTP7rjDjyYoPYXUmfGnViZ6hPv0gsqFsH0Zrufx5BbtIKja\nAnXVuK49ocdIsjMfJ1j/GuRypMZ1CYG8pBbX63jcgBNkQGKL+V9PRY3qI0TJZJLhw4dH3+P2lq2b\nNyv23dHHhO8NHzma8MCKxuSGnEVQnyLYMj/MH3DHXxv+1ncU1O0EZLtPsA63ZQ1BdZrchhwusYXc\nW9MgWU6wcivBst+EG7Q37oEXfk7yqjtwlb8isWFxmGdZHdmdlaROORsSnQnGXAn8X0o6nURuw3yy\nf/o6DLuEYMY0EkDSDSK36hUSLkX92udxb38tYmDXYT2piZ8i+/odJHZUQV7LckDq5K+QeeprYZXr\nulL/p/uhQy+S3bIwPQSk7JtrcW88h9s2ilT5OOq35re1zFlKKn0CmbnP4bqUU1q2AICSiZ8p7LxP\n/Vu+IvEqT3L8Z/I99xVK889yh5fj5q/CZWaQGtKHYHcPHAnChXBIDRtPrtNJBJuXxebZqmhfTqxD\n4UNrc6b7lHcO53K5IJvNBplMJsjlcrHO4VymvpFzOJvLBUEuFzp1c0EQBJnoN3Wm52r3NKpLrnZP\nkAvdumGatWvD9IfQJ6x32KZctj4IHnkkyKXTQS6bCXKZTJCrqw+CTG2QmzLlgyt3167Gn7jnK1bE\nP//3f29+mUEQZDcVnelFOlQoTionErgLLih0Ubz+OgwbVvhqsvGQJvRkBAeqFX3rW9+CG24I3y1t\ni0/+M5ffDNzIP/b978OMGTDL0+i6doXf/hYuu8zL2DXOo4XPtY4uEbbfASTy7UxaUhduQ/nlLxvn\nvWIF9O/f+Pl55zUu86GH4KqrGj8H6NChec9jKNe7DXQsNM0TC3aSWzoTd9SHemTbIUtFoHofNG3a\ntA9+n2HcZAT46lcbP+vbF265JfwA04CoNgMGxOfT1O71D+n5NGDq5ZfD5Zcf9LoATHviCabm+6uA\nmuqvvn2b99wfv82boUePJoF92he/WMhDXbuGvjw/9mrBb0gMPDm+zA+YPhS+fr+0L5XrUPhwiJp+\n55xzzsGuQgEdkPo0M47qnJKSAx9H1RSdeWZwzoAB8Xl8yHFUjSjfX43GrLlxZx8CHSi+bo7pV1z1\nK1KRinTIU9H0K1KRPki64orC7xZG4j9/+22orITS0sLf9uyB3/wm9IMVKaIiUBWpZfTnPxd+nzcP\nXngh3l/0YfuomkMrVsTn80H49AYPhvLywmfl5XDNNY3THp8PoH366cJ35FjsAorLoxXRRwWoygDm\nz59fcJD+waYdO3YwZ86hczLNAatPjx7wne80fv7KK43r9M1vMufDPmF1f9t8003sqKr68OvTDNqx\ndClzPve5/Ut8gHjtQPHRokWL7N+yfaV1QVOrTIcQ5W+6uXufCYtUpCJ9FOnKIAjuea8EHxWg6gpM\nITyIr+bg1qZIRSrSB0RlwBHAk0EQbH2vhB8JoCpSkYrUuqkYnlCkIhXpkKciUBWpSEU65KkIVEUq\nUpEOeSoCVZGKVKRDnj4SQOWc+5JzbqVzbq9zbrZzbuyHVM6JzrmHnXPrnHM559y5MWluds6td85V\nO+eeds4d5f2eds7d6pzb4pzb7Zy73znXo4X1+bZzbo5zbpdzrtI5N9051+jUuANVJ+fc551zbzrn\nduY/LznnzjwYdWmifv+eH7dbvOcHcsy+n6+Dft45WPXJ51fhnLszn191fgyPPZh1ajbtazPgwf4Q\nXiNfA3wKGEJ4Ddc2oNuHUNaZwM3AeYTXeZ3r/f5v+bLPBkYADwLLgVJJ8zvCMIqTgdHAS8CsFtbn\nMeAqYChwNPBIPu/yg1En4BP5PjoSOAr4IeFlskMPRv94dRsLrCC8kfuWgzhm3wfeAroTXinXA+hy\nEOvTCVhJePfmGKAfcDrQ/2DVqUXtOFAFvQ8GnA38P/nuCC80veFDLjdHY6Bq6hboS+V7s26Bbmad\nuuXzmngI1Wkr8JmDWRegHbAYOBV4jkKgOqB1IgSq19/j9wNdn58CM/eR5qDy0P58DmnTzzlXQigF\noitBgrCXngEmHOC69AcO8+qyRZbFSwAAA3dJREFUC3hF6nIc4bYkTbMYeJcPpr6dCI/F2Haw6+Sc\nSzjnLgfaAC8d5P65FfhHEAQzvDoerDoNzLsPljvn7nLO9TmI9TkHeNU59/e8++B159y19uMhwtf7\npEMaqAg1iCRQ6T2vJOzcA0mHEYLEe9WlJ1CXH+im0rSInHMO+E/ghSAIzOdxwOvknBvhnNtNKGF/\nSyhlFx+MuuTrczkwCvh2zM8Ho06zgU8T7qT4PNAf+Kdzru1Bqs8A4AuEGucZhCbcr51zdkTpQeXr\n/aWPyqbkIoWgMAw4YV8JP2RaBIwEOgIXA//tnDvpYFTEOdebELxPD4Kg/mDUwacgCJ6Ur/Odc3OA\n1cClhH13oCkBzAmCwK7gftM5N4IQRO88CPVpER3qGtUWQqd2T+95T2DjAa7LRkL/2HvVZSNQ6pzz\nD8h+X/V1zv0X8HHglCAINhzMOgXhLQorgiCYFwTBd4E3ga8djLoQugW6A6875+qdc/WEzt6vOefq\nCCX+QRkzoyAIdgJLCBcfDkYfbQAWes8WAnaW8kHj6+bQIQ1UeSn5GnCaPcubQKcRrjocyLqsJBwU\nrUsHYJzU5TUg46UZTMgUL7ek3DxInQdMCoLg3UOhTh4lgPRBqsszhKuhowi1vJHAq8BdwMggCFYc\nhDoVkHOuHSFIrT9IffQioeNbaTChlneo8NC+6UB47N/Ph1BlrqYwPGEr0P1DKKstIbOPIlzR+Hr+\ne5/87zfkyz6HcII8CCylcBn3t4TLwacQSvwXafnS8m+B7cCJhNLLPmWS5oDVCfhxvi79CJexf0LI\nwKcejP5poo7+qt+BHrOfAyfl++hjwNOEml3Xg1Sf4wj9id8mDCu5AtgNXH6w+qhF7ThQBb1P5vsi\nYQzHXkIEP+5DKudkQoDKep+/SJr/IFzOrQaeBI7y8kgDvyE0W3cD9wE9WlifuLpkgU956Q5InQhj\ncVbkx2Ej8BR5kDoY/dNEHWcgQHUQxmwaYfjMXsJVsXuQmKWD0UeEboO38uUtAK6JSXNQx21fn+Ix\nL0UqUpEOeTqkfVRFKlKRigRFoCpSkYr0EaAiUBWpSEU65KkIVEUqUpEOeSoCVZGKVKRDnopAVaQi\nFemQpyJQFalIRTrkqQhURSpSkQ55KgJVkYpUpEOeikBVpCIV6ZCnIlAVqUhFOuSpCFRFKlKRDnn6\n/5wMcNxRxxkNAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x15b943aa710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import cv2\n",
    "import matplotlib.pyplot as plt \n",
    "import utils\n",
    "# = 'E:\\BaiduNetdiskDownload\\VOCdevkit\\VOC2007\\JPEGImages\\img_4458.jpg'\n",
    "imgpath =r'E:\\deeplearn\\OCRonline\\chinese-ocr-demo\\test\\8.png'\n",
    "#precess img\n",
    "img = cv2.imread(imgpath)\n",
    "h,w,c = img.shape\n",
    "#zero-center by mean pixel \n",
    "m_img = img - utils.IMAGE_MEAN\n",
    "m_img = np.expand_dims(m_img,axis=0)\n",
    "\n",
    "cls,regr,cls_prod = basemodel.predict(m_img)\n",
    "\n",
    "\n",
    "anchor = utils.gen_anchor((int(h/16),int(w/16)),16)\n",
    "\n",
    "\n",
    "bbox = utils.bbox_transfor_inv(anchor,regr)\n",
    "\n",
    "bbox = utils.clip_box(bbox,[h,w])\n",
    "\n",
    "#score > 0.7\n",
    "fg = np.where(cls_prod[0,:,1]>0.7)[0]\n",
    "select_anchor = bbox[fg,:]\n",
    "select_score = cls_prod[0,fg,1]\n",
    "\n",
    "select_anchor = select_anchor.astype('int32')\n",
    "\n",
    "\n",
    "keep_index = utils.filter_bbox(select_anchor,16)\n",
    "select_anchor = select_anchor[keep_index]\n",
    "select_score = select_score[keep_index]\n",
    "select_score = np.reshape(select_score,(select_score.shape[0],1))\n",
    "\n",
    "\n",
    "nmsbox = np.hstack((select_anchor,select_score))\n",
    "\n",
    "\n",
    "keep = utils.nms(nmsbox,0.3)\n",
    "select_anchor = select_anchor[keep]\n",
    "\n",
    "\n",
    "for i in select_anchor:\n",
    "        cv2.rectangle(img,(i[0],i[1]),(i[2],i[3]),(255,0,0),2)\n",
    "            \n",
    "plt.imshow(img)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(472,)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "select_score.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  2.05762735e-05,   5.25162206e-04,   4.84288787e-04, ...,\n",
       "          1.60110686e-02,   1.68448333e-02,   9.45046451e-03]], dtype=float32)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cls_prod[:,:,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "s = cls_prod[0,:,1] > 0.7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(21090,)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda root]",
   "language": "python",
   "name": "conda-root-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
